The Tube trials live <b>facial recognition</b> tech: Is it a good idea?
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Image Recognition
Samurai Spotlight: SrA Ryan Gaskins [<b>Image</b> 1 of 3]
U.S. Air Force Senior Airman Ryan Gaskins, assigned to the 36th Airlift Squadron, resource advisor and loadmaster, poses with a signed "Installation Sashimono" at Yokota Air Base, Japan, Aug. 14, 2026. Gaskins was selected as the squadron's Samurai Spotlight honoree, recognized for supporting C-130J operations, delivering 274 tons of humanitarian relief supplies to Saipan following Super Typhoon Sinlaku, and providing 11 hours of search-and-rescue coverage alongside the U.S. Coast Guard. (U.S. Air Force photo by Senior Airman Tallon Bratton) | Date Taken: | 08.14.2026 | | Date Posted: | 08.19.2026 22:06 | | Photo ID: | 9878724 | | VIRIN: | 260814-F-TU760-1001 | | Resolution: | 5869x3905 | | Size: | 4.71 MB | | Location: | YOKOTA AIR BASE, TOKYO, JP | | Web Views: | 7 | | Downloads: | 0 | This work, Samurai Spotlight: SrA Ryan Gaskins [Image 3 of 3], by SrA Tallon Bratton, identified by DVIDS, must comply with the restrictions shown on https://www.dvidshub.net/about/copyright.
Direct light-to-token conversion with integrated 2D photosensitive memory | Nature Sensors
Abstract Vision transformers (ViTs) process images as sequences of embedded tokens, yet in existing architectures, tokenization is performed entirely in the digital domain, downstream of image capture. This separation increases energy cost and prevents token formation from occurring where visual information is physically generated. Here we introduce a physical tokenizer that performs analogue light-to-token conversion directly at the sensor level for ViTs. The prototype integrates a 32 × 32 photosensitive memory array of monolayer MoS2 floating-gate phototransistors with peripheral addressing circuitry, enabling optical images to be stored as non-volatile states and selectively combined into patch embeddings in situ, thereby eliminating separate sensing, patch division and patch embedding stages. When deployed in a standard ViT pipeline, the physical tokenizer achieves software-comparable accuracy on CIFAR-10 while reducing energy consumption by 14.3-fold relative to a digital tokenizer. These results establish physical tokenization as an energy-efficient and scalable hardware foundation for edge-intelligent, data-intensive vision systems. This is a preview of subscription content, access via your institution Access options Subscribe to this journal Receive 12 digital issues and online access to articles $119.00 per year only $9.92 per issue Buy this article - Purchase on SpringerLink - Instant access to the full article PDF. USD 39.95 Prices may be subject to local taxes which are calculated during checkout Similar content being viewed by others Subjects Data availability The data supporting the findings of this study are available from the corresponding authors upon reasonable request. Source data are provided with this paper. Code availability The code supporting the findings of this study is available from the corresponding authors upon reasonable request. References - Dosovitskiy, A. et al. An image is worth 16 × 16 words: transformers for image recognition at scale. In Proc. International Conference on Learning Representations (ICLR, 2021). - Liu, Z. et al. Swin
UAFS provides update on success of <b>facial recognition</b> security cameras
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UK ICO finds police <b>facial recognition</b> use mostly compliant with data regulations
UK ICO finds police facial recognition use mostly compliant with data regulations The UK Information Commissioner’s Office says police are using facial recognition in ways that meet their regulatory compliance obligations, for the most part. Their compliance rate is higher with live facial recognition than with retrospective or forensic applications, however, according to the ICO’s findings from audits of five forces in England and Wales. A blog post by Deputy Commissioner for Regulatory Policy Emily Keaney makes the case for strong data protection governance as a pillar of public trust in facial recognition, and therefore suggests police using the technology draw on the audit findings to improve theirs. The ICO makes 107 recommendations overall related to compliance and best practices. The forces accepted all of the recommendations, at least in part, and the regulator gives the police good marks for participating in and cooperating with the audits. Keaney also writes that Home Office and the National Police Chief’s Council (NPCC) told the ICO they are dealing with the demographic differentials found by the National Physics Lab in the legacy Cognitec algorithm released in 2020 with additional staff training, oversight reporting, equality impact assessments and plans to replace the algorithm, presumably to a newer release. In the meantime, Home Office held consultations on the introduction of a legal framework for police use of facial recognition. The ICO participated, calling for greater specificity in guidance for law enforcement. The data protection authority is also contributing guidance for businesses, government bodies and the public to help nurture trust in police use of face biometrics. Scotland and Northern Ireland are also advancing toward more use of facial recognition by police, and the ICO says its recommendations hold for those countries as well. Greater Manchester Police need PND policy Overall, the ICO sees some forces
Profile of Advisory Board Member Daniel Lau, Ph.D. | Vision Systems Design
Meet VSD’s Editorial Advisory Board: Spotlight on Daniel Lau, Ph.D., IEEE Fellow and Pioneer in Machine Vision Innovation Over the next several months, Vision Systems Design will feature profiles of members of its editorial advisory board. We’ll kick off this series with Daniel Lau, Ph.D., a distinguished expert in machine vision and image processing whose career has spanned signal processing, digital halftoning, cutting-edge 3D imaging, and the integration of AI into practical engineering solutions. From his formative education at Purdue University and the University of Delaware to his pioneering research and entrepreneurial ventures, he has consistently pushed the boundaries of imaging technology. Dr. Lau is the Databeam Professor of Electrical and Computer Engineering at the University of Kentucky in Lexington, the university’s director of graduate studies, and a certified professional engineer. His work spans diverse applications, including fingerprint scanning, dairy-industry automation, pipeline inspection, and dental imaging. In 2026, Dr. Lau was elevated to IEEE Fellow in recognition of his contributions to digital printing and 3D imaging. He continues to lead innovative research exploring AI-driven world models for complex process recognition. His collaborative leadership style, enthusiasm for authentic community engagement, and forward-looking approach to AI make him a vital voice in the evolving field of machine vision. To learn more about Dr. Lau and his approach to innovation, I sent him a series of questions. I hope you enjoy this Q&A as much as I do. Editor’s note: The following Q&A may have been edited for style. Vision Systems Design (VSD): Can you share how your career path led you to specialize in machine vision and image processing? Daniel Lau, Ph.D. (DL): Two classes at Purdue, really. I took signal processing from Neal Gallagher, who's a legend in the field, and I was hooked. Then I took image processing from Jan
ClarityCheck's exposed biometric databases present major identity theft, fraud risk
ClarityCheck’s exposed biometric databases present major identity theft, fraud risk Consider where your face might be found. Social media, probably. Maybe internet search. It doesn’t naturally occur to anyone that their face may be stored in a publicly exposed database with no security safeguards to speak of. Unencrypted and freely available, your face could be nicked from that database, paired with fake data and used for identity fraud. Cybersecurity researcher Jeremiah Fowler recently happened upon just such a database. According to what he shared with ExpressVPN, it contained 9,042,977 image files totaling 450.2 GB of data, housing the facial biometrics of adults, teens, and children in folders labeled “faces” and “profiles.” “These included what appeared to be profile images, screenshots, and physical photographs that appeared to have been uploaded for reverse image searches or other identity verification purposes,” Fowler says. “Upon further research, I was able to determine that the files belonged to a U.S.-registered company called ClarityCheck.” Treat biometrics with care they warrant: Fowler ClarityCheck offers reverse phone, email, image and vehicle lookup services. Its website describes “an online digital investigation service that uses reverse image search technology and claims to help users identify individuals, detect catfishing, investigate suspicious online profiles, and perform OSINT-based identity verification.” In the case of a service like ClarityCheck, Fowler says, “the marketed purpose of the platform is the re-identification of individuals by allowing users (anonymous and registered) to upload an image of a person and attempting to connect that image to publicly available information, online profiles, or other identifying records.” For ClarityCheck, a side effect was the mass retention of biometric data that, it turned out, anyone could steal. “I imply no wrongdoing by ClarityCheck, Clarity Check Ltd., or any related entities,” Fowler says. “I do not claim that user data was actively
Police watchdog calls for live <b>facial recognition</b> to tackle football disorder
Police watchdog calls for live facial recognition to tackle football disorder The head of the Scottish police watchdog is calling for the introduction of live facial recognition technology and drones to help combat football-related disorder. HM Chief Inspector of Constabulary in Scotland (HMICS) Craig Naylor has used the publication of his annual report to highlight the need for better use of technology to help fight crime. Naylor described recent football violence, like the disorder between Celtic and Rangers fans at Ibrox in March, as "a situation that cannot continue to be tolerated." He also said the increasing violence in Scotland outside football grounds was likely to require more police deployments. Naylor said: "Elements such as restricting the number of fans allowed to attend matches, banning orders with more rigor, requirements to use modern technologies such as facial recognition to prevent the attendance of banned individuals should all be explored and enacted to ensure that this behaviour is stopped." Live facial recognition technology has been used by police forces at football matches in England. But its deployment remains controversial amid concerns over privacy, civil liberties and the potential for errors in identification. The technology has never been used by Police Scotland but the force has been engaged in a public consultation on its deployment. The report comes after disorder at several games towards the end of last season's Scottish Premiership. This Included high-profile matches between Celtic and Rangers in the Scottish Cup in March and the title decider between Celtic and Hearts in May. Later that day two police officers were seriously injured and 14 arrests were made during trouble in Glasgow city centre as Celtic supporters celebrated the club's Premiership win. Police Scotland's Assistant Chief Constable Tim Mairs said: "We have a duty to use new technologies to safeguard our
Meta files patent for <b>facial recognition</b> glasses that could record automatically
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Skilled labor demand is exploding. AI is both a cause and a solution: NFPA. | Facilities Dive
Dive Brief: - Skilled labor demand has almost doubled over the past three years, driven in part by a rise attributed to AI, according to results of a National Fire Protection Association survey released Tuesday. The organization sets standards for fire and electrical safety in the built environment. - The survey suggests a rise in demand for skilled labor to work on data centers and other types of AI-related infrastructure, pulling trained professionals away from other settings. Roughly a third of respondents to NFPA’s survey cited increased demand for skilled labor related to AI infrastructure, according to NFPA’s survey of 326 skilled trades workers and others in the field, including facility managers. - The results cause concern that as AI infrastructure is prioritized, “skilled workers begin leaving other jobsites to satisfy those needs,” Kyle Spencer, director of NFPA LiNK, said in a statement. At the same time, AI could help workers adapt to these rapid shifts and fill those gaps, with workers already using AI to quickly ensure their work meets the latest code requirements, NFPA says. Dive Insight: The rapid scaling of data centers and digital infrastructure in the U.S. is exacerbating challenges in hiring skilled labor across industries, according to a March report by Randstad North America, which analyzed more than 150 million job postings for key roles between 2022 and 2026 to identify labor demand. For example, it’s now more time-consuming to hire an HVAC professional or an electrician than a software developer. Contributing to that shortage is a generational shift, with seasoned workers retiring and taking the skills that have helped prevent downtime and costly errors with them, Randstad says. Despite a looming retirement cliff for the engineering and technical workforce, vocational training pipelines haven’t kept pace with demand. Conservative estimates suggest a 30% skills gap
DHS tries to lessen constraints of biometric identity verification
DHS tries to lessen constraints of biometric identity verification The Department of Homeland Security is working to mitigate technical challenges tied to biometric identity verification systems, per documents posted Tuesday and earlier this month. DHS built the Biometric Data Collection and Verification System to quantify the performance of data acquired and stored by the agency. The system can identify deficiencies and provides standardized testing measures. In addition to tackling the challenge of identifying failures or inaccuracies in biometric matching algorithms, the BDCVS is meant to speed up data acquisition and delayed retrieval speeds, according to the agency. DHS characterized BDCVS as a “proven system” that improves trust in biometric matching outcomes with applications across screening venues. The agency also developed another new system that aims to address additional shortcomings of typical biometric identification tools used for traveler screening. Biometric verification systems can struggle to properly identify individuals with common first and last names or when birthdays are shared by multiple people, DHS said in its research note. Data input errors, such as misspellings or use of nicknames can also present roadblocks, leading to delays in verification, significant bottlenecks for security personnel and travelers and extended screening process time. In response, researchers from the Transportation Security Administration and the DHS’s Science and Technology Directorate created the Biometric Identity Disambiguation system. BID determines whether an individual matches their identification information by comparing the person’s biometrics and other information, like a driver’s license, to what’s stored in accessible databases. The system then assigns a score that indicates how close of a match the individual is to the documents provided, signalling what level of additional checks are needed to screening personnel. DHS said the technology has potential as a “proven system” across border checkpoints, testing and registration centers and as part of transportation, event
Exclusive | HOA surveillance cameras draw backlash and kill home sales
HOA surveillance cameras secretly installed for ‘neighborhood security’ draw massive backlash — and are killing home sales See more of our coverage in your search results. Add The New York Post on Google Big brother is watching your open house. Homeowners associations across the country are quietly signing up for Flock Safety’s license plate cameras, and the backlash is now strong enough to blow up home sales, kill signed contracts and land cities in court, with New York at the center of the fight. Nowhere is the backlash more raw than in the Adirondacks, where the fight has already toppled a signed contract and sparked open revolt inside a gated community. In Saranac Lake, a resident living behind a gate who protested the cameras in his own neighborhood said the issue isn’t security itself. It’s who gets to look. “The problem I have is not with security cameras. It’s with the Flock system directly. Anyone and their mother can have easy access to this database. The way the data is readily being shared. It is completely unconstitutional,” he told The Post. That anger boiled over at a packed Saranac Lake village board meeting earlier in the year after officials quietly signed a contract for a dozen license plate readers and security cameras using a state grant. Residents said they’d learned about the rollout only after cameras started going up on telephone poles around town. “These cameras are not going to keep us safe,” resident Sandra Kalinowski told the board, drawing applause from the crowd. Another resident, David Lynch, pushed the board to reverse course entirely. “First I believe these cameras are currently in violation of Saranac Lake Police Department policy. Secondly, I believe the public has been misled about Flock’s access to our data. My ask of you tonight is
Daytona Beach debates police use of driver's license photos in <b>facial recognition</b> cases
NEWS Daytona Beach debates police use of driver’s license photos in facial recognition cases Daytona Beach City Commissioners will decide Wednesday whether police can continue using a statewide database of driver’s license photographs as part of facial recognition investigations.
Daytona Beach debates police use of driver's license photos in <b>facial recognition</b> cases
DAYTONA BEACH, Fla. – Daytona Beach City Commissioners will decide Wednesday whether police can continue using a statewide database of driver’s license photographs as part of facial recognition investigations. The vote, scheduled for 6 p.m., comes as law enforcement agencies increasingly use technology to help identify people suspected of crimes — while privacy advocates and residents question how far that technology should go. In Daytona Beach, police use facial recognition software to compare an image of a person to photographs in large databases, including driver’s license photos. The technology itself does not make an arrest or determine that someone is a suspect. Instead, the software generates potential matches that must then be reviewed by a person. For some Daytona Beach residents and visitors, facial recognition is simply another investigative tool. Embry-Riddle student JP Nass said he sees a practical benefit to the technology. “It’s easier to track and see who’s who. It’s better to catch people doing bad things.” Nass said he believes facial recognition should have a legitimate investigative reason behind its use rather than being used simply to identify people. “Only if you have a reason to do it.” But other residents are more concerned about the amount of information law enforcement can collect and how that information is used. Daytona Beach police also use Flock cameras, which can collect information about vehicles traveling through the city. Brian Turnipsed said he is uncomfortable with that type of surveillance, particularly when the technology is operated by a third party. “That I feel is an invasion of privacy. There’s no one manning them. They’re just out there run by a third party.” Turnipsed said there should be limits on how law enforcement tracks people, particularly when there is no probable cause. “I still feel like if they’re going after you,
<b>Facial Recognition</b> Startup ClarityCheck Left 9 Million Face Photos on an Unsecured Server
Facial Recognition Startup ClarityCheck Left 9 Million Face Photos on an Unsecured Server A people-search tool that promises to identify anyone from a single photograph left more than 9 million image files, including close-ups of adults, teenagers, and children, sitting on an unsecured cloud server for months, according to research published this week. The database, traced to the facial-recognition service ClarityCheck, contained roughly 450 GB of images stored in an Amazon S3 bucket without password protection or encryption. Anyone with the right URL could have browsed folders labeled "faces" and "profiles," downloading what appeared to be profile pictures, screenshots, and other photographs. A second misconfiguration also exposed email addresses and phone numbers through the company's website. The findings come from Jeremiah Fowler, an independent security researcher who has documented a long string of exposed databases in recent years. Fowler told WIRED that he discovered the open bucket while investigating ClarityCheck and that his initial attempts to notify the company went unanswered. The database was only secured after WIRED contacted ClarityCheck in July. ClarityCheck is among the growing number of so-called people-finder tools that have proliferated online. The company's website advertises searches by phone number, email address, vehicle identification number, and name. Its photo-search page claims it can "identify anyone in a photo" and locate social media profiles "in seconds." A WIRED reporter who tested the service with their own face watched as the site said it was "scanning facial landmarks" and "mapping unique face geometry" before returning a report that included the reporter's full name, biography, and links to multiple online photos. The company offers deeper reports, including "hidden dating profiles," for a fee. The site requires users to attest that they have permission to upload any photo they submit. But Fowler argues that this safeguard is essentially meaningless for
Possibilities and pitfalls of <b>facial recognition</b> system | Explained
The story so far: The Supreme Court on Tuesday (August 18, 2026) said it will examine the “proportionality” of the use of facial recognition system (FRS) deployed during the students’ protest in the national capital last month after the Delhi Police in an affidavit admitted to its use. The police said that “FRS does not automatically capture, create, generate, or maintain profiles of every individual present at the protest site, nor is it deployed for indiscriminate surveillance or collection of personal information of peaceful protesters unless he has a previous criminal record,” and assured that the use of the technology was “legitimate, bona fide, and proportionate policing measure”. However, the very nature of the system and its possibilities that, if left unchecked, could have extreme implications for public behaviour in the country is concerning. How does facial recognition work? While the use of the AI-powered product of machine learning to monitor a mass gathering is something new for many, facial recognition has been part of the everyday life of human beings around the world for some time. From screen locks in mobile phones to contactless air travel with DIGI Yatra initative, Indian are getting increasingly exposed to various degrees of FRS. The use of the technology can be broadly classified into two avenues, verification and identification. The most common use that has been incorporated into daily lives is verification where the system confirms the identity of a person from previously provided datasets, like in the case of mobile phone security systems. In case of identification processes, the system scans the distinguishable features of people and runs it against a database to determine their identity without them having to reveal it. Verification using FRS is voluntary while identification may or may not be done with the consent of those under the
Bloomington settles lawsuit with man wrongfully arrested due to <b>facial recognition</b> technology
Bloomington settles lawsuit with man wrongfully arrested due to facial recognition technology The City of Bloomington, Minnesota, has settled a lawsuit brought by a man who said he was wrongly arrested back in 2021. Kylese Perryman claims his rights were violated, saying investigators carelessly and incorrectly identified him as the man responsible for a violent felony. He spent five days in jail, 30 days on home monitoring and, after 52 days, charges were eventually dropped His lawyers say this is a case of an investigator comparing surveillance photos of a suspect in a robbery and carjacking to a booking photo of another man and ultimately arresting the wrong person, ultimately the result of faulty facial recognition technology. "So, it is not a positive match, and that is all it does," said Dr. Manjeet Rege, director of the Center for Applied Artificial Intelligence at the University of St. Thomas. "It generates a lead." Lawyers say that Perryman was not near the crime scene. A home surveillance image shows Perryman at a party while two other men carjacked someone, robbed some women and then used those stolen cards at Walmart. Surveillance from Walmart showed the suspect does not have tattoos. Perryman does have tattoos. "I think it becomes a great benefit if it is utilized properly in sync with other regular law enforcement tools," Rege said. "It may become a risk if there are flaws in the process in which it is implemented." Law enforcement's failures alleged in the suit include its failure to conduct a lineup or to contact eyewitnesses to confirm the identification, to consider Perryman's verifiable alibis, to note distinct physical differences between Perryman and the suspect and to promptly drop charges against Perryman when his defense attorney produced clear evidence of his innocence. "I brought this lawsuit because
Amnesty International slams rise of Argentina's 'surveillance state' | Buenos Aires Times
Amnesty International slams rise of Argentina’s 'surveillance state' Massive online surveillance is deterring the right to protest in Argentina, says Amnesty International NGO in latest report. Amnesty International Argentina on Tuesday denounced the growing use of surveillance technologies by President Javier Milei's government against his critics. In a new report (entitled Estado de vigilancia: la expansión del uso de tecnologías de vigilancia masiva por el gobierno de Argentina, or "Sensing the Surveillance State: Argentina’s Expanding Policies and Technologies of Mass Surveillance") Amnesty said the creation of databases of protesters, the monitoring of their social media and the use of facial recognition technology was stifling dissent. Between December 2023, when Milei took office, and December 2025, the Argentine government "implemented a slew of security and intelligence reforms and expanded their use of surveillance technologies," the report said. "These measures constitute an intensification of state monitoring capacities... aimed at controlling and deterring protest and increasing authoritarian practices," it added. Milei's drastic austerity measures have repeatedly sparked mass protests in Buenos Aires and other cities. Amnesty said that the National Security Ministry spent at least US$1.2 million to acquire surveillance technologies between 2024 and 2025. In interviews with Amnesty, a group of journalists, activists, rights defenders and some of the retirees who demonstrate weekly for higher pensions and better healthcare access all said they felt they were being watched. Surveillance technologies “have become an integral part of the state’s control infrastructure,” said Matt Mahmoudi, an Amnesty International researcher and adviser on artificial intelligence and human rights. The Amnesty report said the government had purchased a licence to use facial-recognition technology from Clearview AI, a company “known for the mass exploitation of biometric data without a sufficient legal basis.” In recent years, Clearview has been fined by authorities in France, Greece, Italy and the
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Eyedaptic AI smart glasses deliver 5.7-line acuity gain in AMD
Eyedaptic recently announced results from an independent real-world clinical evaluation demonstrating substantial immediate improvements in functional vision among patients with advanced retinal disease. The findings were presented by David Almeida, MD, MBA, PhD, FRCSC, at the American Retina Forum Annual Meeting, which took place Aug. 5-8 in South Lake Tahoe, California. Let’s start with Eyedaptic. Specializing in vision-enhancement technology, the privately-held company’s products are designed with wearable vision aid software enabled by AI and augmented reality (AR) hardware. Unlike therapies created to slow disease progression, Eyedaptic’s technology is intended to enhance functional vision by digitally optimizing visual information in real time, helping patients utilize their remaining peripheral vision more effectively. Explain how this is done. Through the proprietary Simulated Natural Vision Software, which works by optimizing a patient’s functional (remaining) peripheral vision via pixel manipulation—“simulating” clearer vision. - The intent: To give patients an improved quality of life with a hands-free, easy-to-wear glasses design (take a look at the clinical research supporting the tech). Which patients is this technology designed for? The company is currently targeting patients diagnosed with age-related macular degeneration (AMD) and diabetic retinopathy (DR). And that software is included in these smart glasses? Indeed. In fact, it’s included in Eyedaptic's entire line of AI-enhanced eyewear: the EYE5, EYE6—and as of March 2026—the EYE7. Among the features of these glasses: - Lightweight design (weighing in at less than 3 oz) - Facial detection capabilities - Auto-zoom mode for viewing text in various situations - Contrast enhancement controls (for additional image enhancements) - 2-in-1 wearable and hand-held magnifier - EyeSwitch technology As a side note: Prior iterations of the company’s products also encompassing this patented technology include the EYE2, EYE3, and EYE4. Are they cleared by the FDA? According to Eyedaptic, its smart glasses are Class I exempt medical