Category Archives: Neurotechnology

Syndicate Market Research recently launched a study report on theglobal Face Recognition Technology marketproject light on the significant drifts and vigorous cannon into the evolution of the trade, which includes the restraints, market drivers, and opportunities. The report talks about the competitive environment prevailing in the Face Recognition Technology market worldwide. The report lists the key players in the market and also provides insightful information about them such as their business overview, product segmentation, and revenue segmentation. In 2018, the global Face Recognition Technology market size was xx million US$ and it is expected to reach xx million US$ by the end of 2026, with a CAGR of xx% during 2019-2026.

The Specialist team offers you a Free PDF Sample copy of the research report as per your Querry/Requirement, additionally, impact analysis of COVID-19 provides on Face Recognition Technology industry development

The authors of the report have segmented the global Face Recognition Technology market as per vendor list, product, application, and region.Segments of the global Face Recognition Technology market are analyzed on the basis of market share, production, consumption, revenue, CAGR, market size, and more factors.The analysts have characterized leading industry players of the universal Face Recognition Technology market, keeping in vision their recent developments, market sales, share, revenue, product portfolio, areas covered, and other aspects.

The top players including Overview, Financials, Product Portfolio, Business Strategy, and Recent Developments:Nviso, Daon, Idemia, Keylemon, Nuance Communications, Ayonix, IBM, Neurotechnology, Animetrics, Cognitec Systems, NEC, 3M, Gemalto, Techno Brain, Herta Security, Crossmatch, Facefirst Inc.

How data can be gathered?

With all the information congregated and examined using SWOT analysis, there is a vivacious picture of the competitive landscape of the Global Face Recognition Technology Market. Openings for the future market development were revealed and preoccupied competitive dangers likewise textured. The movement and tendency of this market were considered and it illustrates that there was outstanding strategic supervision observed. By the grasping market foundation and using the determined excellence, methodologies, and inclinations of other driving markets for references, market statistics was understood.

Globally, the global Face Recognition Technology market has been fragmented into various regions such asNorth America, Latin America, Middle East, Asia-Pacific, Africa, and Europe. Furthermore, it gives a holistic snapshot of the competitive landscape across the world. To get a better outlook in the businesses, it offers various strategies and methodologies. The global Face Recognition Technology market has been presented in a clear, concise and professional manner which helps to better understanding readers. Different infographics have been incorporated in the report, to offer the graphical presentation of some significant facts and figures of the market.

North America:U.S.Canada, Rest of North AmericaEurope:UK, Germany, France, Italy, Spain, Rest of EuropeAsia Pacific:China, Japan, India, Southeast Asia, Rest of Asia PacificLatin America:Brazil, Argentina, Rest of Latin AmericaThe Middle East and Africa:GCC Countries, South Africa, Rest of Middle East & Africa

Points Covered in The Report:Global Face Recognition Technology market 2021 studies afford a primary overview of the enterprise which includes definitions, classifications, programs, and industry chain structure. The Global Face Recognition Technology Market analysis is supplied for the global markets which include improvement developments, competitive landscape evaluation, and key areas development status. Development policies and plans are discussed in addition to manufacturing procedures and value systems are also analyzed. This document also states import/export consumption, delivery and call for Figures, value, price, sales, and gross margins.

Types: 2D Facial Recognition, 3D Facial Recognition

Applications: Intelligent Signage, Photo Indexing and Sorting, Photo Indexing and Sorting, Criminal Investigation, Homeland Security, Business Intelligence, ID Management, Physical Security

Chapter 1Introduction

Chapter 2Industry Cost Structure and Economic Impact

Chapter 3Rising Trends and New Technologies with Major Manufacturers Profiles/Analysis

Chapter 4Global Face Recognition Technology Market Analysis, Trends, Growth Factor, Porters Five Forces Analysis

Chapter 5Face Recognition Technology Market Supply (Production), Consumption, Export, Import and Business with Potential Analysis by Region

Chapter 6Global Face Recognition Technology Market Production, Revenue (Value), Price Trend by Type and Application

Chapter 7Marketing Strategy Analysis, Distributors/Traders

Chapter 8Industrial Demand-Supply Chain, Sourcing Strategy and Downstream Buyers

Chapter 9Development Trend of Analysis, Market Effect Factors Analysis

Chapter 10Research Findings and Conclusion

This seriously explored report introduction has been set up progressively speech, delivering considerable consideration towards the COVID-19 episode that has of late unleashed phenomenal harm across businesses, deteriorating development.

Face Recognition Technology Market study report analyses the impact of Coronavirus (COVID-19) on the leading manufacturers in the industry. In December 2019, the first case of the Covid-19 virus was reported in China. From that point forward, the illness has spread to almost 180+ nations around the globe.

The WHO declared it a public health emergency. The global effects of coronavirus disease (Covid-19) is already being felt and will have a significant impact on the Face Recognition Technology market by 2020.

The outbreak of Covid-19 has influenced numerous variables, for example, flight undoings and disconnection, the revelation of the highly sensitive situation in numerous nations, gigantic inventory network speed, securities exchange vulnerability, closure of restaurants, ban on all indoor events, declining business guarantees, growing population panic and panic among the population and Uncertainty about the future.

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Face Recognition Technology Trend Analysis, Market Revenue, Business Strategies, COVID Vaccine Impact The Courier - The Courier

The titans of Silicon Valley say that the brain-computer interface revolution is coming, and neurotech devices will soon meld mind and machine, allowing us to communicate effortlessly with our computers and even one another just by using our thoughts.

But I believe their prognostications arent likely to come to fruition anytime soon.

Elon Musk invested $100 million into his neurotech startup, Neuralink, to develop an implantable device he has referred to as a Fitbit in your skull with tiny wires. Kernel recently unveiled a version of its brain-recording helmet, with its founder predicting that the device would be in every home by 2033. And Facebook is working on brain-computer interface (BCI) technology to enable brain-to-text typing.

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In this new world of private neurotech development, company demos are live-streamed on YouTube and have the flavor of techno-optimism that involves proclamations about a future we have yet to see but one that we are assured will come to pass. Data are sparse; rhetoric about making the world a better place is heavy.

I am a neuroethicist, someone who studies ethical and social implications of advances in neurotechnology. So I frequently get asked about its development. Should we be worried that companies like Facebook, Neuralink, Kernel, and others helmed by individuals who have previously launched paradigm-shifting technology are working on capturing data from our brains?

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My answer: I doubt we will have accurate, mind-reading consumer devices in the near future. There are practical constraints that will likely hamper the development and adoption of these devices. These limitations more on them in a minute are nowhere to be seen in media coverage or industry proclamations like Neuralinks recent live demo, in which Musk and other employees expressed hopes that their product would relieve human suffering, provide superhuman vision, allow for telepathy, cure paralysis, solve and prevent practically every disease, upload memories, explain consciousness, remove fear, and achieve symbiosis with artificial intelligence.

Neuroscience is far from understanding how the mind works much less having the ability to decode it. In many studies of brain-computer interfaces, it appears as if a device is essentially free reading someones thoughts, la Uri Geller. But a deeper look often reveals a method to the magic. For example, many researchers use electrophysiological neural signals as proxies for user communication. Heres a crude analogy: If an Apple Watch user was instructed to flick her wrist to the right as a proxy for saying no, and left for saying yes, we could decode communication by using data from the watchs accelerometer. Similarly, in BCI research, users are often instructed to pay attention to a particular part of the screen or to imagine performing a specific action as a proxy for yes or no. Impressive, but not a true decoding of thought.

It is unlikely that the public will adopt a consumer device requiring neurosurgery. Today, the most accurate brain-computer interfaces use recordings from electrodes that have been implanted into the brain, rather than recordings from outside the skull. But such implantation requires neurosurgery. Although neurotech companies are working to develop safer methods of implantation Neuralink, for example, is building a robot that can inject tiny electrode threads into the brain there will never be a risk-free method of implanting a recording device into the human brain.

Musk has envisaged Neuralink as akin to LASIK, a cosmetic procedure for which an individual assumes a small surgical risk in order to eliminate the need to wear glasses. But a neurotech device would have to add significant value for a consumer to get one implanted in her skull.

Just because we can collect brain data, that data wont necessarily add value for consumers. Consumer brain-recording devices have been on the market for roughly 15 years. They were initially marketed for users to control objects such as computer cursors, foam balls, and even a toy helicopter with their thoughts. Today they are more commonly advertised for wellness. But these devices have never become mainstream, likely because they are not entirely accurate and consumers have found little use for them.

This failure to find a meaningful use for brain data raises questions about what, exactly, consumers will do with even more neural information. Will the time-domain functional near-infrared spectroscopy measurements that Kernel is working on add enough value to our daily lives that we will be willing to walk around while wearing brain-sensing helmets?

Helmets and other headgear face an uphill battle to adoption. Consumers have shown time and again that they are reluctant to adopt products that look funny (ahem, Google Glass). The problem with brain-computer interfaces is that measuring neural signals usually requires a contraption that sits on the skull or in it. Aside from socially acceptable headwear like headphone and baseball caps, there are few contraptions that consumers are likely to readily embrace. This barrier, which is often glossed over, is readily illustrated by looking to the history of failed consumer neurotechnology devices.

It may be more taxing to control a device with a BCI than without it. As I type this, Im not paying attention to the movement of my fingers across the keyboard. So, while typing with my brain may be a neat party trick, in a gimmicky look, ma, no hands sort of way, will it be practical for healthy individuals to use their focused, conscious attention to move cursors and peck out letters on a keyboard? A neurotech device would need to demonstrate superiority over current methods of human-computer interaction to gain market traction.

Though these limitations are not insurmountable, there are few, if any, brain-computer interfaces in development that circumvent them. So while much of the media coverage about these devices has centered on privacy concerns, I believe that we need to be realistic about the relative risks. The reams of personal data being gathered about each of us from our phones, web browsers, credit cards, and smart homes are currently being aggregated and sold with little oversight. Some of this information, particularly my search engine history, emails, and notes, are more revealing about who I am than my neural data may ever be.

The hype over brain privacy may distract us from the more pragmatic, albeit less sexy, issues that may arise in the near term. My colleague Robert Thibault and I have argued that the problem with consumer brain-computer interfaces on the market today is not that they can record rich, private, revealing information from the brain. Its that they are falsely claiming to be able to do such things, and consumers might confuse bunk science with real science. Similarly, future devices may be oversold to consumers without clear evidence of effectiveness.

Whatever the future holds for consumer brain-computer interfaces, two groups will likely be winners as a result of Silicon Valleys obsession with neurotechnology. The first group is scientists who study the brain the only group that has a demonstrable interest in all kinds of neural signals. More accurate and mobile recording devices could lead to more neural data that can be measured in the wild instead of on undergraduates using bulky laboratory machinery. The second group is neurosurgeons and their patients, as technological innovation in neurosurgical devices may prove a side benefit of Musks desire to merge humanity with AI.

It will take time to realize these benefits. Were still smack in the middle of a neurotech bubble fueled by venture capital, one that will inevitably yield an increasing number of prophecies about our sci-fi future. So the next time you hear a tech entrepreneur predict that brain-computer interfaces will liberate humanity, remember that these devices are not yet on or in our heads, and may not be anytime soon.

Anna Wexler is an assistant professor of medical ethics and health policy at the University of Pennsylvanias Perelman School of Medicine.

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A skeptic's take on Neuralink and other consumer neurotech - STAT - STAT

HAMILTON, Ontario A new study, released today in the scientific journal Advances in Therapy is providing critical evidence that neurotechnology combined with saliva testing can drastically reduce the likelihood of falsely determining cannabis impairment due to THC residual detection. The independent, blind study, conducted by KGK Science on behalf of Zentrela, confirms that Zentrelas pioneering neurotechnology is the industrys most accurate test for detecting and quantifying actual cannabis psychoactive effects, and unlocks the potential for new testing protocols for law enforcement and employers.

There is limited understanding of the brain effects caused by cannabis psychoactive properties, and limited means to accurately quantify those effects. Law enforcement and employers have relied upon traditional methods for detecting and quantifying THC-compound levels using body fluids such as saliva, blood and urine. However, it is well known that there is no direct correlation between THC concentration levels in body fluids and whether an individual is actually experiencing psychoactive effects associated with THC. This means law enforcement or employers cannot accurately confirm impairment, leading to the possibility of inaccurate determinations of cannabis impairment. These determinations can negatively affect the reputation and employment of individuals who may be consuming legal cannabis products responsibly.

The KGK Science study describes the performance of Zentrelas Cognalyzer neurotechnology to detect and quantify cannabis psychoactive effects and shows that when combined with an oral fluid test for detecting and quantifying THC levels, neurotechnology can drastically improve the accuracy of testing and minimize the likelihood of falsely determining cannabis impairment due to THC residual detection.

For the next phase of its research, Zentrela will collaborate with strategic research partners to correlate its objective cannabis psychoactive effect scale with driving and cognitive performance data to determine a psychoactive effect level (cutoff level) that indicates when it is not advisable for consumers to drive or work.

The ability to definitively measure the psychoactive effects of cannabis allows us to begin addressing the problems related to cannabis consumption that affect the industry and the broader community, says Zentrela Chief Science Officer, Dr. Dan Bosnyak. A scientifically objective cannabis psychoactive-effect test has endless applications for cannabis producers and product manufacturers, for law enforcement, and for employers in many industries.

An available scientific database of cannabis product effects also unlocks one of the most significant challenges facing producers and brands in the recreational cannabis industry: availability of regulatory-compliant cannabis effect data.

Without this information, producers cannot differentiate their products and inform consumers about the different effects created by their recreational cannabis products, retailers cannot meet their CANCELL mandate to educate consumers and promote responsible cannabis use and of course, consumers are missing out on the information that they require to make more accurate and informed decisions about recreational cannabis consumption, says Zentrela CEO, Israel Gasperin. The data we are generating will give retailers and producers access to a centralized source of scientifically-derived product effect information, which will benefit the entire cannabis industry value chain.

Until this point, there simply hasnt been an accurate, science-based test for quantifying cannabis psychoactive effects. We have clearly demonstrated that neuroscience powered by artificial intelligence (AI) can accurately detect and quantify the psychoactive effects of cannabis. This represents a huge potential for Zentrela to become the definitive source for specific, science-based data on cannabis product effects for the entire industry. And we are still at the beginning of our journey. There is no reason we cannot apply this proven neurotechnology to other drugs and industries.

About ZentrelaZentrela Inc. is advancing the understanding of the brain effects of recreational cannabis and is creating the worlds largest scientific database of cannabis product effects. Visit us at http://www.zentrela.com.

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HAMILTON, Ontario A new study, released today in the scientific journal Advances in Therapy is providing c - mg Magazine

Using a range of analysis methodologies, the facial Recognition study offers detailed and systematic insights into global business trends and dynamics. The most up-to-date information on business risks and the supply chains role in the industry is also included in this report. Likewise, the facial Recognition research report looks at a range of opportunities and risks. This report contains historical, current, and future industry statistics to help in the analysis of key market factors in the global facial Recognition market.

Overall, the report offers detailed coverage of the facial Recognition industry and presents main market trends. This research gives historical and forecasts market size, demand and production forecasts, end-use demand details, price trends, and company shares of the leading facial Recognition producers to provide exhaustive coverage of the market.

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The global facial Recognition market provides in-depth market analysis as well as pictorial representations of key statistical findings. The global facial Recognition market study includes key data on recent and emerging drivers, knowledge, evolving technologies, and other important factors. For a specified time period, the research report offers demand forecasts for the industrial sector. It also provides key insights into market dynamics and the current economic conditions, as well as key information for readers to profit from different business trends.

facial Recognition Market Top Players: NEC Corporation, Aware, Inc., Ayonix Corporation, Cognitec Systems GmbH, Gemalto NV, Animetrics, Daon, Id3 Technologies, Idemia, Innovatrics, Megvii, Neurotechnology, NVISO SA, StereoVision Imaging, Inc., Techno Brain Group, etc.

This is the latest report on the facial Recognition market offers impact of COVID-19 epidemic. This study examines the impact of the pandemic on demand and the supply chain, as well as the industrys financial condition. Variations in market dynamics and current developments in a post-COVID-19 setting are also covered, as well as a future outlook.

The report also assesses the effect of global health crises on the facial Recognition market in the short and long term. This research report also includes an overview of the current and historical business situation to help explain the industrys growth trend over the course of the survey. As part of the studys preparation, extensive tests and studies were carried out.

Read Complete Report With TOC: https://www.adroitmarketresearch.com/industry-reports/facial-recognition-market

Based on application, the market has been segmented into: By Application, End User (BFSI, media & entertainment, telecom & IT, Government & Defense, Healthcare, Retail & E-commerce)

Based on Type, the market has been segmented into: by Technology (2D facial recognition, 3D facial recognition, facial analytics recognition), Application, End User (BFSI, media & entertainment, telecom & IT, Government & Defense, Healthcare, Retail & E-commerce)

Geographically, this facial Recognition report is segmented into several key regions, with sales, revenue, market share (%) and growth rate (%) of the facial Recognition in these regions, covering

North America

South America

Asia-Pacific

Europe

Southeast Asia

The Middle East

This report can be extremely useful for consumers who want to gain a thorough understanding of the target industry. The research reports main goal is to help customers gain a deeper understanding of the target markets segmentation, influential trends, definition, growth potential, and challenges.

Important Features of the Market Report

Global key players operating situation (sales, growth rate, revenue, and gross margin) of the facial Recognition industry.

Different product types and applications of the global industry, market revenue of each type & application by revenue.

Market sales, revenue forecast by countries and regions of the global facial Recognition industry.

Upstream raw materials, downstream major consumers, manufacturing equipment, and industry chain study of the target industry.

Key drivers influencing market development, opportunities, challenges, and risk analysis.

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facial Recognition Market Trends, Growing Demand and Forecasts to 2026 | NEC Corporation, Aware, Inc., Ayonix Corporation, Cognitec Systems GmbH,...

National Neurotechnology Initiative Act seeks to accelerate development of new treatments for brain and nervous system conditions

SAN FRANCISCO & WASHINGTON, D.C., March 12 - A team of prominent members of both houses of Congress introduced today the National Neurotechnology Initiative (NNTI) Act, a bill designed to foster new discoveries and accelerate the development of new and safer treatments for the one in three Americans living with a brain-related illness, injury or disease.

The sponsors of the NNTI Act, Senator Patty Murray (D-WA) and Representatives Patrick J. Kennedy (D-RI 1st) and Ileana Ros-Lehtinen (R-FL 18th), have called upon Congress to reverse the growing economic burden generated by brain-related illness, which exceeds $1 trillion per year in the U.S. due to healthcare costs and lost income.

"The huge numbers speak for themselves: There are 100 million Americans suffering from a brain-related illness, with an enormous economic burden that continues to grow as the population ages," said Zack Lynch, Executive Director of the Neurotechnology Industry Organization. "For a modest investment, Congress has the opportunity to streamline research efforts, accelerate the development of new treatments, promote innovation and job creation by small businesses and have a meaningful impact on the lives of those suffering from devastating diseases and injuries."

Designed to increase private investment and accelerate the development of treatments reaching the market, the NNTI employs targeted increases in funding to improve Federal research coordination and ease bottlenecks that inhibit the development of treatments for brain-related illnesses. The bill accomplishes these goals with less than 4 percent of the total Federal neuroscience research budget - $200 million - and reflects a more balanced disease-cost to research-dollars-expended ratio.

"While our ability to understand how the brain works grows each day, our ability to understand and repair brain illnesses remains limited," said Senator Murray. "For the millions of Americans that suffer from a brain related illness, and the thousands of Americans coming home from Iraq and Afghanistan with Traumatic Brain Injury and PTSD, a new federal commitment to research and treatment can't wait. This bill will place a premium on sharing the information researchers gain everyday and will support ongoing but underfunded programs at NIH."

"With so many Americans suffering from brain-related illnesses, it is crucial for us as a society to maximize our efforts and continue learning about the many facets of the brain, leading to a healthier life for all Americans," said Congressman Patrick Kennedy.

"This legislation will turn America into a nation where brain injuries and diseases are tackled through innovative technology, state of the art medical equipment and top notch neuroscientists. Together we can make this a reality," said Congresswoman Ileana Ros-Lehtinen.

The National Neurotechnology Initiative is designed to address four key bottlenecks that slow the process of developing brain treatments:

The bill also creates a research center that will focus on the ethical, legal, and social implications of neurotechnology.

Have an idea that this legislation will support? Get ideas on how to launch it in our Innovation Center.

Follow this legislation: Senate Bill 586 and House Bill 1483

Read the original here:

Neurotech Bill Introduced in Both Senate and House of Representatives - Epilepsy Foundation

(Credit: Unsplash)

This article is brought to you thanks to the collaboration ofThe European Stingwith theWorld Economic Forum.

Author: Ankita Moss, Researcher, Neuroethics and Neurotech Innovation Collaboratory, Emory University & Karen Rommelfanger, Associate Professor and Director, Neuroethics and Neurotech Innovation Collaboratory, Emory University

For centuries, the inner workings of the brain and human mind have conjured great imagination and allure; neuroscience has promised insights into one of the most prized features of human life, the cognitive experience.

Today, neuroscience has edged into territories once thought only to inhabit the realms of science fiction. Daily reports include stories ranging from jaw-dropping to tear-jerking, including research on head transplants, techniques that demonstrate restoration of brain function in brains of pigs six hours after their death, the potential of brain imaging to be used for lie detection (or even testimony) in the courtroom, and given hope for the possibility of restoring a damaged memory or augmenting a healthy, intact one.

Mapping brain circuitry has also paved the way for brain computer interface (BCI) technology, which promises to help restore or revive the brain and body. New abilities to read and write information into the brain via recording and stimulation technologies have enormous potential for improving quality of life for those sick and suffering. Todays brain interfaces have been used to connect multiple animal and human brains and may even be able to restore movement after years of paralysis. Consumers even beyond the hospital are eager to use safer and smaller versions of the tech for themselves for work, exercise, and sharpening mental acuity.

But interfacing with the brain can feel deeply and exceptionally personal the brain encodes our experience and is a critical site for decision-making. We are seeing a new flavour of messy ethical concerns surfacing issues of autonomy, mental privacy, and the fragility of foundational features of identity, all of which were once thought to be sacred, impenetrable, and immutable.

Cutting-edge neuroscience requires cutting-edge ethics that can keep pace with the rapid evolution of neuroscience and neurotechnologies.

The World Economic Forum was the first to draw the worlds attention to the Fourth Industrial Revolution, the current period of unprecedented change driven by rapid technological advances. Policies, norms and regulations have not been able to keep up with the pace of innovation, creating a growing need to fill this gap.

The Forum established the Centre for the Fourth Industrial Revolution Network in 2017 to ensure that new and emerging technologies will helpnot harmhumanity in the future. Headquartered in San Francisco, the network launched centres in China, India and Japan in 2018 and is rapidly establishing locally-run Affiliate Centres in many countries around the world.World Economic Forum | Centre for the Fourth Industrial R

The global network is working closely with partners from government, business, academia and civil society to co-design and pilot agile frameworks for governing new and emerging technologies, including artificial intelligence (AI), autonomous vehicles, blockchain, data policy, digital trade, drones, internet of things (IoT), precision medicine and environmental innovations.

Learn more about the groundbreaking work that the Centre for the Fourth Industrial Revolution Network is doing to prepare us for the future.

Want to help us shape the Fourth Industrial Revolution? Contact us to find out how you can become a member or partner.

The pandemic has made crystal clear just how critical ethics is to determining action in the face of evolving scientific information. Neuroethics, which explores and analyzes the ethical, legal, and social implications of neuroscience might just be one of the most essential tools to advance and accelerate the most impactful neuroscience.

The commercialization of BCI technology, for example, has been coupled with the rise of alternative non-invasive approaches such as headsets for meditation or performance enhancement. Such non-invasive devices can be scalable to the public and relatively easy to use. But the risk-benefit calculus drastically changes in the commercial realm: when potential user harm is hedged against a promise of an entertainment and/or subtle wellness improvement in an otherwise healthy individual. This promise, along with the tensions and neurohype in this space are exemplified by projects like Elon Musks Neuralink. Elon Musks Neuralink is not the first neurotech startup to promise commercial use BCI, and it will not be the last.

In our lab, the Neuroethics and Neurotech Innovation Collaboratory led by Global Neuroethics co-chair and NIH BRAIN Initiative Neuroethics member Dr. Karen Rommelfanger, we conducted one-one interviews with over 20 international neurotech innovators, discussing value conflicts in areas from return on investment (ROI), to data privacy, to societal implications, to maximizing positive the impact of neurotechnology.

We found that neuro-innovators are generally aware of the sensitive nature of brain research and interventions; the powerful possibilities of brain technologies are a driving force for innovators. Neurotech innovators believe that neuroscience is poised to generate the highest societally beneficial impact. But naturally, they are deeply concerned with issues related to privacy, access, and ownership, and often have strong beliefs about using science to empower societies by allowing individuals to overcome hardship and reach their full potential. However, while they clearly are interested in and concerned about neuroethical issues, they arent typically familiar with or aware that such a field exists.

A reflection of this orientation is that they often had difficulty seeing the full scope of what ethics could offer. Instead ethics was seen as narrowly as red tape, often at odds with return on investment. Ethics was also misunderstood as solely compliance that could be handled by legal teams. In our research, it was clear that innovators want incentives for integrating ethics within the innovation process, not punitive measures for incorporating ethics. By conflating ethics with compliance, companies are missing opportunities. Stuck relying on legal teams who do not have the tools to identify and surface biases, assumptions, and value conflicts, neurotech innovators had not yet been introduced to the notion that, by integrating a neuroethics strategy into innovation life cycles, they could actually advance and accelerate high impact neurotechnologies.

Overall, neurotech innovators should not be mistaken as only concerned about money and fast innovation. But there are numerous missed opportunities for powerful societal impact by failing to orient their conversations around ethics in more expansive ways, beyond risk mitigation.

We suggest three solutions for neuroethically aligned neurotech design.

This is also a call to think of ethics beyond risk mitigation and toward social impact. A good strategy could fit in the entire innovation life cycle from the grassroots idea and prototype phase to ethical marketing for tech deployment.There is a small, but substantial global community of neuroethics experts. There are many individuals who can help advise in less formal to formal ways. One of the authors established the first-of-its kind neurotech ethics strategy and consulting firm. Neurotech innovators and ethicists need to come together to collaborate and create these paths forward. When done intentionally, neuroethics can help advance and accelerate the most societally impactful neurotech by uncovering the exponential benefits of bringing ethically-oriented innovation to market.

A neuroethics mindset can facilitate return on investments (ROI) both financially and toward recognizing that neurotechs grand engineering challenges are ones that go hand in hand with addressing socio-ethical ones. We can learn for example, from wireless communication tech being engineered to incorporate privacy safeguards. In our research, we learned that innovators often feel torn about personal values and the timeline for ROI. While many believed end users should own their data, the collected data were immediately valuable, even more so than the tech interfaces they were developing. The financial pressure is not conducive to protecting the privacy of end-users. What if business proposals to investors could be reoriented toward also protecting end-user data, particularly neurodata? This orientation would ease the ethical tensions neurotech innovators face and also protect end-user privacy.

This is where neuroethics capacity building and creating cultures of ethical inquiry can help. Much of the reported value of neuroethics in the neurotech innovation process comes from the uncertainty neuro-entrepreneurs feel toward their decisions, especially those with presently undeterminable consequences. This uncertainty derives from the unpredictability of a future influenced by neurotechnology. To neuro-entrepreneurs, the brain is a new and largely undiscovered frontier. By being proactive through establishing a culture of neuroethics, each member of the company can be ethically aware and attuned to value conflicts, enabled to act quickly, and collectively mobilized to solve issues before they become larger ones. Innovators are acutely aware that nothing will tank their work faster than creating a tech that doesnt align with end-user values. Some tech cultures like Apple and Google to some extent have already found ways to enculturate their communities with ethics. Theyve not only used a reputation of trust to the benefit of maintaining their consumer-base, but also to recruit the best talent. Weve also seen an explosion of attention for AI ethics, but our neurotech ecosystem still is lagging with neuroethics integration.

Based on our research, there is a clear call to action for the leadership of neurotech companies and startups to work with neurotech-ethicists and neuroethicists more broadly. This point was recently reinforced in a session of the 2020 International Neuroethics Society Conference featuring Facebooks Mark Chevillet and Nia Therapeutics Dan Rizzuto. Researchers and keynote Ruha Benjamin from Princeton participating in the conference also pointed out a need to be mindful of perpetuating bias, such as those resulting in racial discrimination inherent in unthoughtful tech design. Neuroethicists can collaboratively help identify these ethical blindspots.

We also recognize that the neuroethics community has failed to sufficiently connect with our private sector neuroscientists, neurotech innovators, and neuro-entrepreneurs. Were working on building community and a shared vocabulary between neuroethicists and neurotech innovators. As we continue to identify neuroethical pain points, well began mapping bottlenecks and roadblocks when aligning neuroethics with the neuro-innovation process.

If theres one consistent thread about humans, its that they arent just interested in survival; instead they are constantly seeking to improve themselves as individuals and innovate for a greater collective society. We believe neuroethics is the key to innovating in the neurotech ecosystem, and were ready to help.

Read more from the original source:

How neuroethics can advance innovations for positive social impact - The European Sting

By Avi Asher-Schapiro

BERLIN (Thomson Reuters Foundation) A turning point for Rafael Yuste, a neuroscientist at New Yorks Columbia University, came when his lab discovered it could activate a few neurons in a mouses visual cortex and make it hallucinate.

The mouse had been trained to lick at a water spout every time it saw two vertical bars, and researchers were able to prompt it to drink even with no bars in sight, said Yuste, whose team published a study on the experiment in 2019.

We could make the animal see something it didnt see, as if it were a puppet, he told the Thomson Reuters Foundation in a phone interview. If we can do this today with an animal, we can do it tomorrow with a human for sure.

Yuste is part of a group of scientists and lawmakers, stretching from Switzerland to Chile, who are working to rein in the potential abuses of neuroscience by companies from tech giants to wearable startups.

Following his teams discovery, he launched the NeuroRights Initiative, which advocates five neuro-rights to protect how a persons brain data is accessed and used, including a right to mental privacy and to free will.

Right now, its the wild west, Yuste said.

In Chile, senate member Guido Girardi is pushing to translate those principles into law, with a bill that would give legal protection to a suit of neuro-rights, and a complementary reform to the countrys constitution.

This month, the National Commission for Scientific and Technological Research began debating Girardis proposal, which got unanimous support from parliament in December 2020.

His office hopes the bill will be adopted later in the year.

If this technology is industrialized without the proper regulations and rules, it will threaten fundamental human autonomy, he said in a phone interview.

Meanwhile, the Organisation for Economic Co-operation and Development (OECD) has issued its own neurotechnology guidelines, noted Marcello Ienca, a researcher at ETH Zurichs Health Ethics and Policy Lab, who works on the OECD project.

Usually people only start talking about ethics and regulations after a big scandal, but with neurotech I hope we can take on these questions before that scandal, he said.

SCIENCE-FICTION SCENARIOS

Advances in brain science like those made by Yustes team have made it possible to penetrate the brain using censors and implants and access some degree of neural activity.

The U.S. Food and Drug Administration has approved deep brain stimulation procedures implanting electrodes in the brain to treat a range of disorders from Parkinsons disease to epilepsy.

And major tech firms, from Facebook to Tesla, are working on computer-brain interfaces to allow consumers to control devices with their thoughts, while some smaller companies sell wearable devices to monitor brain activity.

But warnings of science-fiction scenarios of for-profit mind control are overblown for a line of research that is still so young, said Karen Rommelfanger, director of the neuroethics program at Emory University in Atlanta.

Yes, the science will get better, not worse, she said. But exactly how it develops is up in the air.

Ienca at ETH Zurich said major ethical issues could arise if the data commercial neurotech devices cllect is widely shared and analyzed without proper safeguards, he said.

We already have digital biomarkers that can indicate if someone is predisposed to developing dementia. Lets say (that) data is shared with a prospective employer, you could face discrimination on the job market, he said.

In 2018, Ienca published a review of six commercially available neuromonitoring headsets in the journal Nature Biotechnology.

He found that the electroencephalography (EEG) data gathered by the devices as they measure electrical activity in the brain could be leaked online, sold to third parties, or subjected to uses that consumers did not consent to.

This also concerns Adam Molnar, the co-founder of neurotech start-up Neurable, which is developing headphones that measure EEG to help users track brain activity and emotions like burnout.

When Neurable launches a new device, he said, it pledges not to sell user data, and only uses collected data to improve its own products.

We want to be the good guys, he said, adding that he hopes the move will help set the tone for other neurotech firms.

DATA HARVESTING

Rommelfanger at Emory is wary of moving too quickly to regulate brain tech, which she said could stifle innovation.

She recommends direct engagement with startups working on commercial devices, encouraging them to develop privacy-conscious and ethically-minded products.

Girardi favors strict regulation. We didnt regulate the big social media and internet platforms in time, and it costs us. We have lost control of all kinds of data, from our location to our romantic interests its all up for sale, he said.

My proposals would give the status of your mind data the same as your organs, like your heart, he added. No one can interfere with it.

If we allow for all this brain data to be taken, who knows what the consequences will be? Well have algorithms deciding what it means to be happy, Girardi said.

Tim Brown, a neuroethics expert at the University of Washington, said the data currently being collected is not powerful enough to do that.

A lot of that brain data is basically noise, he said.

But, he noted, scientists are working on algorithms to decode and analyze the data gleaned from EEG and functional magnetic resonance imaging (fMRI) scans, hoping to build computer models that can interpret an individuals mental state.

He predicted the same dynamics present in the social media or search industry where companies offer a service for free in return for permission to harvest user data will likely surface in neurotech.

That could lead to serious consequences for privacy in the coming years, Brown warned, with companies linking users social media behavior to their brain images in real time to craft ads or other messages.

He also worries about how neurotechnology might exacerbate existing patterns of discrimination and racism.

In his research, he has warned of the possibility of mandatory neurointerventions, when institutions like schools or prisons might deploy neurotechnology to assess mental states.

Are we going to see a situation where prisoners are asked to put their heads in a box, and they are scanned to see if they are eligible for parole based on an algorithmic interpretation of their brain?, Brown asked.

What will the impact of that be on Black and brown people, who we know are already disproportionately (represented) in these institutions.

Yuste says policymakers around the world need to start contemplating these issues now.

He has been in touch with members of President Joe Bidens administration and the United Nations about neuro-rights and related issues.

Its not about patching the law, he said. These technologies affect the core of what it means to be human the only way to tackle this is with new human rights.

(Reporting by Avi Asher-Schapiro @AASchapiro, Editing by Jumana Farouky and Zoe Tabary. Please credit the Thomson Reuters Foundation, the charitable arm of Thomson Reuters, that covers the lives of people around the world who struggle to live freely or fairly. Visit http://news.trust.org)

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Analysis-Out of my mind: Advances in brain tech spur calls for 'neuro-rights' - Global Banking And Finance Review

This report studies the Cloud-Based ABIS System Market with many aspects of the industry like the market size, market status, market trends and forecast, the report also provides brief information of the competitors and the specific growth opportunities with key market drivers. Find the complete Cloud-Based ABIS System Market analysis segmented by companies, region, type and applications in the report.

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Market Segment by Regions, regional analysis covers

North America (United States, Canada and Mexico)

Europe (Germany, France, UK, Russia and Italy)

Asia-Pacific (China, Japan, Korea, India and Southeast Asia)

South America (Brazil, Argentina, Colombia etc.)

Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)

Research objectives:

To study and analyze the global Cloud-Based ABIS System market size by key regions/countries, product type and application, history data from 2013 to 2017, and forecast to 2027.

To understand the structure of Cloud-Based ABIS System market by identifying its various sub segments.

Focuses on the key global Cloud-Based ABIS System players, to define, describe and analyze the value, market share, market competition landscape, SWOT analysis and development plans in next few years.

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To strategically profile the key players and comprehensively analyze their growth strategies.

The report lists the major players in the regions and their respective market share on the basis of global revenue. It also explains their strategic moves in the past few years, investments in product innovation, and changes in leadership to stay ahead in the competition. This will give the reader an edge over others as a well-informed decision can be made looking at the holistic picture of the market.

Table of Contents: Cloud-Based ABIS System Market

Key questions answered in this report

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Using an ordinary light microscope, MIT engineers have devised a technique for imaging biological samples with accuracy at the scale of 10 nanometers which should enable them to image viruses and potentially even single biomolecules, the researchers say.

The new technique builds on expansion microscopy, an approach that involves embedding biological samples in a hydrogel and then expanding them before imaging them with a microscope. For the latest version of the technique, the researchers developed a new type of hydrogel that maintains a more uniform configuration, allowing for greater accuracy in imaging tiny structures.

This degree of accuracy could open the door to studying the basic molecular interactions that make life possible, says Edward Boyden, the Y. Eva Tan Professor in Neurotechnology, a professor of biological engineering and brain and cognitive sciences at MIT, and a member of MITs McGovern Institute for Brain Research and Koch Institute for Integrative Cancer Research.

If you could see individual molecules and identify what kind they are, with single-digit-nanometer accuracy, then you might be able to actually look at the structure of life. And structure, as a century of modern biology has told us, governs function, says Boyden, who is the senior author of the new study.

The lead authors of the paper, which appears today inNature Nanotechnology, are MIT Research Scientist Ruixuan Gao and Chih-Chieh Jay Yu PhD 20. Other authors include Linyi Gao PhD 20; former MIT postdoc Kiryl Piatkevich; Rachael Neve, director of the Gene Technology Core at Massachusetts General Hospital; James Munro, an associate professor of microbiology and physiological systems at University of Massachusetts Medical School; and Srigokul Upadhyayula, a former assistant professor of pediatrics at Harvard Medical School and an assistant professor in residence of cell and developmental biology at the University of California at Berkeley.

Low cost, high resolution

Many labs around the world have begun usingexpansion microscopysince Boydens lab first introduced it in 2015. With this technique, researchers physically enlarge their samples about fourfold in linear dimension before imaging them, allowing them to generate high-resolution images without expensive equipment. Boydens lab has also developed methods forlabelingproteins, RNA, and other molecules in a sample so that they can be imaged after expansion.

Hundreds of groups are doing expansion microscopy. Theres clearly pent-up demand for an easy, inexpensive method of nanoimaging, Boyden says. Now the question is, how good can we get? Can we get down to single-molecule accuracy? Because in the end, you want to reach a resolution that gets down to the fundamental building blocks of life.

Other techniques such as electron microscopy and super-resolution imaging offer high resolution, but the equipment required is expensive and not widely accessible. Expansion microscopy, however, enables high-resolution imaging with an ordinary light microscope.

In a 2017 paper, Boydens lab demonstrated resolution of around 20 nanometers, using a process in which samples wereexpanded twicebefore imaging. This approach, as well as the earlier versions of expansion microscopy, relies on an absorbent polymer made from sodium polyacrylate, assembled using a method called free radical synthesis. These gels swell when exposed to water; however, one limitation of these gels is that they are not completely uniform in structure or density. This irregularity leads to small distortions in the shape of the sample when its expanded, limiting the accuracy that can be achieved.

To overcome this, the researchers developed a new gel called tetra-gel, which forms a more predictable structure. By combining tetrahedral PEG molecules with tetrahedral sodium polyacrylates, the researchers were able to create a lattice-like structure that is much more uniform than the free-radical synthesized sodium polyacrylate hydrogels they previously used.

The researchers demonstrated the accuracy of this approach by using it to expand particles of herpes simplex virus type 1 (HSV-1), which have a distinctive spherical shape. After expanding the virus particles, the researchers compared the shapes to the shapes obtained by electron microscopy and found that the distortion was lower than that seen with previous versions of expansion microscopy, allowing them to achieve an accuracy of about 10 nanometers.

We can look at how the arrangements of these proteins change as they are expanded and evaluate how close they are to the spherical shape. Thats how we validated it and determined how faithfully we can preserve the nanostructure of the shapes and the relative spatial arrangements of these molecules, Ruixuan Gao says.

Single molecules

The researchers also used their new hydrogel to expand cells, including human kidney cells and mouse brain cells. They are now working on ways to improve the accuracy to the point where they can image individual molecules within such cells. One limitation on this degree of accuracy is the size of the antibodies used to label molecules in the cell, which are about 10 to 20 nanometers long. To image individual molecules, the researchers would likely need to create smaller labels or to add the labels after expansion was complete.

They are also exploring whether other types of polymers, or modified versions of the tetra-gel polymer, could help them realize greater accuracy.

If they can achieve accuracy down to single molecules, many new frontiers could be explored, Boyden says. For example, scientists could glimpse how different molecules interact with each other, which could shed light on cell signaling pathways, immune response activation, synaptic communication, drug-target interactions, and many other biological phenomena.

Wed love to look at regions of a cell, like the synapse between two neurons, or other molecules involved in cell-cell signaling, and to figure out how all the parts talk to each other, he says. How do they work together and how do they go wrong in diseases?

The research was funded by Lisa Yang, John Doerr, Open Philanthropy, the National Institutes of Health, the Howard Hughes Medical Institute Simons Faculty Scholars Program, the Intelligence Advanced Research Projects Activity, the U.S. Army Research Laboratory, the US-Israel Binational Science Foundation, the National Science Foundation, the Friends of the McGovern Fellowship, and the Fellows program of the Image and Data Analysis Core at Harvard Medical School.

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Method offers inexpensive imaging at the scale of virus particles - ScienceBlog.com

LOS ANGELES, United States: QY Research offers an overarching research and analysis-based study on, Global Face Recognition Software Market Report, History and Forecast 2015-2026, Breakdown Data by Companies, Key Regions, Types and Application. Analysts have used primary and secondary research methodologies to determine the path of the market. The data includes historic and forecast values for a well-rounded understanding.The researchers and analysts who have prepared the report used an advanced research methodology and authentic primary and secondary sources of market information and data. It is a phenomenal compilation of important studies that explore the competitive landscape, segmentation, geographical expansion, and revenue, production, and consumption growth of the global Face Recognition Software market. Players can use the accurate market facts and figures and statistical studies provided in the report to understand the current and future growth of the global Face Recognition Software market. The report offers an in-depth assessment of key market dynamics, the competitive landscape, segments, and regions in order to help readers to become better familiar with the global Face Recognition Software market.

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Competitive Landscape

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TOC

1 Market Overview of Face Recognition Software1.1 Face Recognition Software Market Overview1.1.1 Face Recognition Software Product Scope1.1.2 Market Status and Outlook1.2 Global Face Recognition Software Market Size Overview by Region 2015 VS 2020 VS 20261.3 Global Face Recognition Software Market Size by Region (2015-2026)1.4 Global Face Recognition Software Historic Market Size by Region (2015-2020)1.5 Global Face Recognition Software Market Size Forecast by Region (2021-2026)1.6 Key Regions, Face Recognition Software Market Size YoY Growth (2015-2026)1.6.1 North America Face Recognition Software Market Size YoY Growth (2015-2026)1.6.2 Europe Face Recognition Software Market Size YoY Growth (2015-2026)1.6.3 China Face Recognition Software Market Size YoY Growth (2015-2026)1.6.4 Rest of Asia Pacific Face Recognition Software Market Size YoY Growth (2015-2026)1.6.5 Latin America Face Recognition Software Market Size YoY Growth (2015-2026)1.6.6 Middle East & Africa Face Recognition Software Market Size YoY Growth (2015-2026) 2 Face Recognition Software Market Overview by Type2.1 Global Face Recognition Software Market Size by Type: 2015 VS 2020 VS 20262.2 Global Face Recognition Software Historic Market Size by Type (2015-2020)2.3 Global Face Recognition Software Forecasted Market Size by Type (2021-2026)2.4 Holistic Matching Method2.5 feature-based Method2.6 Skin Texture Analysis2.7 Hybrid Types2.8 Other 3 Face Recognition Software Market Overview by Application3.1 Global Face Recognition Software Market Size by Application: 2015 VS 2020 VS 20263.2 Global Face Recognition Software Historic Market Size by Application (2015-2020)3.3 Global Face Recognition Software Forecasted Market Size by Application (2021-2026)3.4 Corporate & Residential Security3.5 Public Transport3.6 Entertainment Software3.7 Public Security & Justice3.8 Self-service Equipment3.9 Attendance & Conference3.10 Financial Services3.11 Other 4 Global Face Recognition Software Competition Analysis by Players4.1 Global Face Recognition Software Market Size (Million US$) by Players (2015-2020)4.2 Global Top Manufacturers by Company Type (Tier 1, Tier 2 and Tier 3) (based on the Revenue in Face Recognition Software as of 2019)4.3 Date of Key Manufacturers Enter into Face Recognition Software Market4.4 Global Top Players Face Recognition Software Headquarters and Area Served4.5 Key Players Face Recognition Software Product Solution and Service4.6 Competitive Status4.6.1 Face Recognition Software Market Concentration Rate4.6.2 Mergers & Acquisitions, Expansion Plans 5 Company (Top Players) Profiles and Key Data5.1 Aware (US)5.1.1 Aware (US) Profile5.1.2 Aware (US) Main Business and Companys Total Revenue5.1.3 Aware (US) Products, Services and Solutions5.1.4 Aware (US) Revenue (US$ Million) (2015-2020)5.1.5 Aware (US) Recent Development and Reaction to Covid-195.2 BioID (DE)5.2.1 BioID (DE) Profile5.2.2 BioID (DE) Main Business and Companys Total Revenue5.2.3 BioID (DE) Products, Services and Solutions5.2.4 BioID (DE) Revenue (US$ Million) (2015-2020)5.2.5 BioID (DE) Recent Development and Reaction to Covid-195.3 Idemia (FR)5.5.1 Idemia (FR) Profile5.3.2 Idemia (FR) Main Business and Companys Total Revenue5.3.3 Idemia (FR) Products, Services and Solutions5.3.4 Idemia (FR) Revenue (US$ Million) (2015-2020)5.3.5 Leidos (US) Recent Development and Reaction to Covid-195.4 Leidos (US)5.4.1 Leidos (US) Profile5.4.2 Leidos (US) Main Business and Companys Total Revenue5.4.3 Leidos (US) Products, Services and Solutions5.4.4 Leidos (US) Revenue (US$ Million) (2015-2020)5.4.5 Leidos (US) Recent Development and Reaction to Covid-195.5 Visage Technologies (SE)5.5.1 Visage Technologies (SE) Profile5.5.2 Visage Technologies (SE) Main Business and Companys Total Revenue5.5.3 Visage Technologies (SE) Products, Services and Solutions5.5.4 Visage Technologies (SE) Revenue (US$ Million) (2015-2020)5.5.5 Visage Technologies (SE) Recent Development and Reaction to Covid-195.6 Cloudwalk (CN)5.6.1 Cloudwalk (CN) Profile5.6.2 Cloudwalk (CN) Main Business and Companys Total Revenue5.6.3 Cloudwalk (CN) Products, Services and Solutions5.6.4 Cloudwalk (CN) Revenue (US$ Million) (2015-2020)5.6.5 Cloudwalk (CN) Recent Development and Reaction to Covid-195.7 M2SYS (US)5.7.1 M2SYS (US) Profile5.7.2 M2SYS (US) Main Business and Companys Total Revenue5.7.3 M2SYS (US) Products, Services and Solutions5.7.4 M2SYS (US) Revenue (US$ Million) (2015-2020)5.7.5 M2SYS (US) Recent Development and Reaction to Covid-195.8 Gemalto (NZ)5.8.1 Gemalto (NZ) Profile5.8.2 Gemalto (NZ) Main Business and Companys Total Revenue5.8.3 Gemalto (NZ) Products, Services and Solutions5.8.4 Gemalto (NZ) Revenue (US$ Million) (2015-2020)5.8.5 Gemalto (NZ) Recent Development and Reaction to Covid-195.9 StereoVision Imaging (US)5.9.1 StereoVision Imaging (US) Profile5.9.2 StereoVision Imaging (US) Main Business and Companys Total Revenue5.9.3 StereoVision Imaging (US) Products, Services and Solutions5.9.4 StereoVision Imaging (US) Revenue (US$ Million) (2015-2020)5.9.5 StereoVision Imaging (US) Recent Development and Reaction to Covid-195.10 Cognitec Systems (GE)5.10.1 Cognitec Systems (GE) Profile5.10.2 Cognitec Systems (GE) Main Business and Companys Total Revenue5.10.3 Cognitec Systems (GE) Products, Services and Solutions5.10.4 Cognitec Systems (GE) Revenue (US$ Million) (2015-2020)5.10.5 Cognitec Systems (GE) Recent Development and Reaction to Covid-195.11 HID Global (US)5.11.1 HID Global (US) Profile5.11.2 HID Global (US) Main Business and Companys Total Revenue5.11.3 HID Global (US) Products, Services and Solutions5.11.4 HID Global (US) Revenue (US$ Million) (2015-2020)5.11.5 HID Global (US) Recent Development and Reaction to Covid-195.12 NEC (JP)5.12.1 NEC (JP) Profile5.12.2 NEC (JP) Main Business and Companys Total Revenue5.12.3 NEC (JP) Products, Services and Solutions5.12.4 NEC (JP) Revenue (US$ Million) (2015-2020)5.12.5 NEC (JP) Recent Development and Reaction to Covid-195.13 NVISO (BE)5.13.1 NVISO (BE) Profile5.13.2 NVISO (BE) Main Business and Companys Total Revenue5.13.3 NVISO (BE) Products, Services and Solutions5.13.4 NVISO (BE) Revenue (US$ Million) (2015-2020)5.13.5 NVISO (BE) Recent Development and Reaction to Covid-195.14 Daon (US)5.14.1 Daon (US) Profile5.14.2 Daon (US) Main Business and Companys Total Revenue5.14.3 Daon (US) Products, Services and Solutions5.14.4 Daon (US) Revenue (US$ Million) (2015-2020)5.14.5 Daon (US) Recent Development and Reaction to Covid-195.15 MEGVII (CN)5.15.1 MEGVII (CN) Profile5.15.2 MEGVII (CN) Main Business and Companys Total Revenue5.15.3 MEGVII (CN) Products, Services and Solutions5.15.4 MEGVII (CN) Revenue (US$ Million) (2015-2020)5.15.5 MEGVII (CN) Recent Development and Reaction to Covid-195.16 Ayonix Face Technologies (IN)5.16.1 Ayonix Face Technologies (IN) Profile5.16.2 Ayonix Face Technologies (IN) Main Business and Companys Total Revenue5.16.3 Ayonix Face Technologies (IN) Products, Services and Solutions5.16.4 Ayonix Face Technologies (IN) Revenue (US$ Million) (2015-2020)5.16.5 Ayonix Face Technologies (IN) Recent Development and Reaction to Covid-195.17 Innovatrics (SK)5.17.1 Innovatrics (SK) Profile5.17.2 Innovatrics (SK) Main Business and Companys Total Revenue5.17.3 Innovatrics (SK) Products, Services and Solutions5.17.4 Innovatrics (SK) Revenue (US$ Million) (2015-2020)5.17.5 Innovatrics (SK) Recent Development and Reaction to Covid-195.18 HYPR (US)5.18.1 HYPR (US) Profile5.18.2 HYPR (US) Main Business and Companys Total Revenue5.18.3 HYPR (US) Products, Services and Solutions5.18.4 HYPR (US) Revenue (US$ Million) (2015-2020)5.18.5 HYPR (US) Recent Development and Reaction to Covid-195.19 Fujitsu (JP)5.19.1 Fujitsu (JP) Profile5.19.2 Fujitsu (JP) Main Business and Companys Total Revenue5.19.3 Fujitsu (JP) Products, Services and Solutions5.19.4 Fujitsu (JP) Revenue (US$ Million) (2015-2020)5.19.5 Fujitsu (JP) Recent Development and Reaction to Covid-195.20 Kairos (US)5.20.1 Kairos (US) Profile5.20.2 Kairos (US) Main Business and Companys Total Revenue5.20.3 Kairos (US) Products, Services and Solutions5.20.4 Kairos (US) Revenue (US$ Million) (2015-2020)5.20.5 Kairos (US) Recent Development and Reaction to Covid-195.21 Animetrics (US)5.21.1 Animetrics (US) Profile5.21.2 Animetrics (US) Main Business and Companys Total Revenue5.21.3 Animetrics (US) Products, Services and Solutions5.21.4 Animetrics (US) Revenue (US$ Million) (2015-2020)5.21.5 Animetrics (US) Recent Development and Reaction to Covid-195.22 id3 Technologies (FR)5.22.1 id3 Technologies (FR) Profile5.22.2 id3 Technologies (FR) Main Business and Companys Total Revenue5.22.3 id3 Technologies (FR) Products, Services and Solutions5.22.4 id3 Technologies (FR) Revenue (US$ Million) (2015-2020)5.22.5 id3 Technologies (FR) Recent Development and Reaction to Covid-195.23 Smilepass (GB)5.23.1 Smilepass (GB) Profile5.23.2 Smilepass (GB) Main Business and Companys Total Revenue5.23.3 Smilepass (GB) Products, Services and Solutions5.23.4 Smilepass (GB) Revenue (US$ Million) (2015-2020)5.23.5 Smilepass (GB) Recent Development and Reaction to Covid-195.24 Techno Brain (SA)5.24.1 Techno Brain (SA) Profile5.24.2 Techno Brain (SA) Main Business and Companys Total Revenue5.24.3 Techno Brain (SA) Products, Services and Solutions5.24.4 Techno Brain (SA) Revenue (US$ Million) (2015-2020)5.24.5 Techno Brain (SA) Recent Development and Reaction to Covid-195.25 Neurotechnology (LT)5.25.1 Neurotechnology (LT) Profile5.25.2 Neurotechnology (LT) Main Business and Companys Total Revenue5.25.3 Neurotechnology (LT) Products, Services and Solutions5.25.4 Neurotechnology (LT) Revenue (US$ Million) (2015-2020)5.25.5 Neurotechnology (LT) Recent Development and Reaction to Covid-195.26 Fulcrum Biometrics (US)5.26.1 Fulcrum Biometrics (US) Profile5.26.2 Fulcrum Biometrics (US) Main Business and Companys Total Revenue5.26.3 Fulcrum Biometrics (US) Products, Services and Solutions5.26.4 Fulcrum Biometrics (US) Revenue (US$ Million) (2015-2020)5.26.5 Fulcrum Biometrics (US) Recent Development and Reaction to Covid-195.27 FaceFirst (US)5.27.1 FaceFirst (US) Profile5.27.2 FaceFirst (US) Main Business and Companys Total Revenue5.27.3 FaceFirst (US) Products, Services and Solutions5.27.4 FaceFirst (US) Revenue (US$ Million) (2015-2020)5.27.5 FaceFirst (US) Recent Development and Reaction to Covid-195.28 Certibio (BR)5.28.1 Certibio (BR) Profile5.28.2 Certibio (BR) Main Business and Companys Total Revenue5.28.3 Certibio (BR) Products, Services and Solutions5.28.4 Certibio (BR) Revenue (US$ Million) (2015-2020)5.28.5 Certibio (BR) Recent Development and Reaction to Covid-19 6 North America Face Recognition Software by Players and by Application6.1 North America Face Recognition Software Market Size and Market Share by Players (2015-2020)6.2 North America Face Recognition Software Market Size by Application (2015-2020) 7 Europe Face Recognition Software by Players and by Application7.1 Europe Face Recognition Software Market Size and Market Share by Players (2015-2020)7.2 Europe Face Recognition Software Market Size by Application (2015-2020) 8 China Face Recognition Software by Players and by Application8.1 China Face Recognition Software Market Size and Market Share by Players (2015-2020)8.2 China Face Recognition Software Market Size by Application (2015-2020) 9 Rest of Asia Pacific Face Recognition Software by Players and by Application9.1 Rest of Asia Pacific Face Recognition Software Market Size and Market Share by Players (2015-2020)9.2 Rest of Asia Pacific Face Recognition Software Market Size by Application (2015-2020) 10 Latin America Face Recognition Software by Players and by Application10.1 Latin America Face Recognition Software Market Size and Market Share by Players (2015-2020)10.2 Latin America Face Recognition Software Market Size by Application (2015-2020) 11 Middle East & Africa Face Recognition Software by Players and by Application11.1 Middle East & Africa Face Recognition Software Market Size and Market Share by Players (2015-2020)11.2 Middle East & Africa Face Recognition Software Market Size by Application (2015-2020) 12 Face Recognition Software Market Dynamics12.1 Covid-19 Impact: Industry Trends12.2 Covid-19 Impact: Market Drivers12.3 Covid-19 Impact: Market Challenges12.4 Porters Five Forces Analysis 13 Research Finding /Conclusion 14 Methodology and Data Source14.1 Methodology/Research Approach14.1.1 Research Programs/Design14.1.2 Market Size Estimation14.1.3 Market Breakdown and Data Triangulation14.2 Data Source14.2.1 Secondary Sources14.2.2 Primary Sources14.3 Disclaimer14.4 Author List

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Face Recognition Software Market Analysis, Trend, COVID-19 Impact, Industry Overview |Aware (US), BioID (DE), Idemia (FR), Leidos (US) The Market...