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Tokyo ward's <b>facial recognition</b> camera trial raises privacy concerns

Tokyo ward's facial recognition camera trial raises privacy concerns (Mainichi Japan) TOKYO (Kyodo) -- A Tokyo ward has installed outdoor AI cameras with facial recognition capabilities to help locate missing children and elderly people, a move aimed at improving public safety but also raising privacy concerns. Arakawa Ward installed 33 artificial intelligence-equipped security cameras on utility poles along the main street and elsewhere near JR Nippori Station in April to test whether the technology could speed up searches for missing persons. The busy area around the station is frequented by commuters, students and foreign residents. If a child or elderly person with dementia goes missing, family members can ask the ward to conduct an AI-assisted search by providing a photograph. The AI then scans recorded footage for people closely matching the image. The ward believes that this is the first outdoor deployment of AI facial recognition security cameras by a local Japanese government, and hopes that it will help to find missing people more quickly. Police stations in Arakawa receive about 100 reports each year of missing children and elderly people with dementia. Until now, police officers and ward officials have searched on foot around train stations and other locations. The footage is stored for seven days. Only a small number of staff have access via a dedicated computer in a locked room at the ward office, and officials say it is used solely to search for missing people. AI-equipped security cameras are also being introduced elsewhere in Japan, but for different purposes. Hyogo Prefecture and Tokyo's Adachi Ward plan to introduce cameras capable of detecting people lingering in entertainment districts in an effort to curb touting. The use of facial recognition technology has prompted privacy concerns in Japan and overseas. The European Union's AI Act prohibits the real-time collection

Congress targets underage betting with <b>facial</b> age estimation bill

Congress targets underage betting with facial age estimation bill Online sportsbooks and prediction markets would have to analyze a user’s face to estimate whether the person is old enough to gamble under bipartisan legislation introduced Wednesday in the U.S. House. The Facial Recognition to Protect Children Act would require an age check either when a user logs into a platform or before the user places a wager or trades an event contract. The measure is aimed at children who gain access to accounts belonging to parents, siblings, or other adults after those accounts have already passed conventional identity checks. Rep. Josh Gottheimer, a New Jersey Democrat, introduced the bill with eight cosponsors, including Republican Reps. Jeff Van Drew, Nick LaLota, and Bruce Westerman. Democratic cosponsors are Kristen McDonald Rivet, Jimmy Panetta, Darren Soto, Tom Suozzi, and Ritchie Torres. In May, the House Committee on Oversight and Government Reform opened an inquiry into Polymarket and Kalshi, pressing the two prediction market companies for records on identity verification, geographic restrictions, suspicious trading, and the handling of markets tied to military operations, geopolitical events, and political contests. Despite the name of the new legislation, the technology described by Gottheimer’s office is more accurately called facial age estimation than facial recognition. The proposed system would examine facial structure and patterns to estimate the user’s age. Gottheimer’s office said the technology would not store the person’s identity or personal biometric information. The distinction matters because online sportsbooks already verify information about an account holder and use geolocation systems to determine whether a wager is being placed in a jurisdiction where the platform may operate. Those controls do not necessarily establish that the person holding the phone during a later session is the adult who opened the account. Gottheimer said a child can therefore enter a

Clarivate Powers USPTO AI <b>Image</b> Trademark Search | CLVT Stock News

USPTO Launches AI Image Search in Trademark Search System, Powered by Clarivate Rhea-AI Summary Clarivate (NYSE: CLVT) is providing AI-assisted image search technology to power a new image search capability in the U.S. Patent and Trademark Office’s TM Search trademark system. Users can now upload images and compare them against the U.S. trademark register to help identify visually similar existing marks, improving search efficiency and result quality. AI-generated analysis. How Rhea-AI works. Not financial advice. Positive - None. Negative - None. Previous AI Reports | Date | Event | Sentiment | 24h Move | Catalyst | |---|---|---|---|---| | Apr 28 | AI product launch | Positive | +2.0% | Launch of Nexus Connect institutional AI gateway for trusted research access. | | Mar 26 | AI benchmark report | Positive | -2.4% | Release of Clarivate AI50 list highlighting leading AI invention organizations. | | Mar 10 | AI integration announcement | Positive | +1.1% | Cortellis Regulatory Intelligence integration with Claude via Model Context Protocol. | | Feb 03 | AI webinar | Positive | -20.4% | Webinar on proprietary data and AI capabilities for research and life sciences. | | Jan 22 | AI assistant launch | Positive | +3.6% | Announcement of Clarivate Nexus academic assistant for AI-connected library access. | 24h Move is the share-price change in the day after each event; other market factors may also have contributed. AI-tagged announcements have produced mixed reactions for Clarivate, with an average move of about -3.21% despite generally positive catalysts. Key Terms ai assisted image search technical trademark register regulatory image recognition technical artificial intelligence technical intellectual property regulatory AI-generated analysis. How Rhea-AI works. Not financial advice. Using AI‑assisted image search technology delivered by Clarivate, the updated USPTO search enables applicants, practitioners, and registrants to upload an image

FAAN set to transform domestic air travel with V-Pass <b>facial recognition</b> system

The Federal Airports Authority of Nigeria (FAAN) is rolling out V-Pass, a biometric identity verification system designed to make domestic air travel faster, safer and more seamless. Developed in partnership with M/S Verxid Technologies Limited, the system will let passengers confirm their identities through facial recognition, reducing the need to rely on physical ID documents at airports. The rollout was reviewed during a strategic meeting between FAAN and Verxid Technologies Limited, where both sides discussed deployment plans, security measures and ways to improve the passenger experience. FAAN said the initiative shows its commitment to using technology to improve passenger facilitation and aviation security across domestic airports. V-Pass will give travellers a secure digital identity through a one-time enrolment process. | | | |---| Nigerian passengers will register with their NIN and facial biometric capture, while foreign passengers will enrol using international passports through OCR and biometric authentication. The system will check passengers before they enter restricted areas and again before boarding. This dual-verification process is meant to prevent impersonation, unauthorized access and identity fraud, while giving security agencies greater confidence in passenger authentication. During rollout, passengers will be able to use self-service kiosks or get help from FAAN staff. E-Gates will automate access to controlled areas, reduce queues and improve passenger flow. Developers say biometric processing will take less than 30 seconds after enrolment, while first-time registration will take about one minute. V-Pass will also give airlines secure access to flight schedules, passenger manifests and boarding statistics through a digital platform. FAAN will benefit from a Central Management System that tracks passenger movement, generates analytics and supports future integration with other airport systems. FAAN and Verxid said data privacy remains central to the project. READ ALSO: FAAN defends airport cab tariff hike amid protest against vehicle upgrade policy The system

FAAN To Introduce <b>Facial Recognition</b> System For Domestic Air Travellers

The Federal Airports Authority of Nigeria (FAAN) has announced plans to introduce V-Pass, a biometric facial recognition system designed to make passenger processing faster, safer and more seamless across its domestic airports. According to FAAN, the new technology will allow passengers to verify their identities through facial recognition after a one-time enrolment, reducing reliance on physical identification documents and shortening queues through automated electronic gates. The authority said the system is expected to enhance airport security while improving the overall travel experience for domestic passengers. FAAN added that V-Pass has been developed with data privacy at its core and is compliant with the Nigeria Data Protection Regulation (NDPR). ADVERTISEMENT The agency described the initiative as part of its commitment to delivering smarter, technology-driven airport services and said nationwide sensitisation and rollout updates would be announced in due course.

Monroe County weighs <b>facial</b>-<b>recognition</b> disclosure law

POLITICS Monroe County weighs facial-recognition disclosure law Kerria Weaver Rochester Democrat and Chronicle July 16, 2026, 6:08 a.m. ET Monroe County lawmakers are considering a local law that would require retailers to tell customers when biometric identification technology is being used in stores. Legislator Rachel Barnhart introduced a proposal earlier this year in February requiring commercial establishments to present an in-store notice of their use of biometric technology to customers.

A unified domain adaptation framework for traffic light <b>recognition</b> in adverse scenes

Abstract Traffic light recognition under adverse scenes is a fundamental yet challenging task for intelligent driving systems, where domain shift caused by variations in weather, illumination, and geographic conditions often leads to significant performance degradation. To address this issue, this paper proposes a unified domainadaptive traffic light recognition framework, termed DA-TLR, to improve cross-domain generalization and robustness. Unlike existing methods that treat feature alignment in a decoupled manner, DA-TLR formulates domain adaptation as a unified modeling problem across both image-level and instance-level discrepancies. Specifically, DA-TLR is built upon the YOLOv5-l architecture and integrates a teacher-student module, an image-level adaptation module, and a domain adaptation loss for joint optimization. The teacher-student module employs a knowledge distillation strategy to generate high-confidence pseudo labels, facilitating instance-level feature alignment. The image-level adaptation module combines bidirectional pseudo-image transformation and dynamic masking to reduce appearance discrepancies and enhance robustness against domain-specific variations. Extensive experiments on multiple domain adaptation scenarios, including foggy, rainy, nighttime, and crossregional conditions, demonstrate that DA-TLR consistently outperforms existing methods. In particular, the proposed method achieves mAP50 scores of 89.57% and 79.03% in cross-fog and cross-rain tasks, respectively, approaching the upper bound of target-domain supervised training. Further analysis indicates that jointly modeling multi-level domain discrepancies is more effective than treating them independently. Overall, DA-TLR provides an effective and practical solution for robust traffic light recognition under adverse scenes, and offers a promising direction for domain-adaptive perception in real-world intelligent driving systems. During the embargo period (the 12 month period from the publication of the Version of Record of this article), the Accepted Manuscript is fully protected by copyright and cannot be reused or reposted elsewhere. As the Version of Record of this article is going to be / has been published on a subscription basis, this Accepted Manuscript will be available for reuse

Face <b>Recognition</b> Gates Introduced at Ikebukuro Station

Face Recognition Gates Introduced at Ikebukuro Station    Tokyo, July 15 (Jiji Press)--Hitachi Ltd. and Tobu Railway Co. on Wednesday introduced a facial recognition system at ticket gates at Ikebukuro Station in Tokyo's Toshima Ward.    Passengers can pass through the ticket gates hands-free if they register their facial data and commuter pass information in advance.    The companies hope to encourage other railway operators to adopt the system, which can be installed by simply adding cameras and other equipment to existing ticket gates.    The system was jointly developed in cooperation with three ticket gate manufacturers, including Toshiba Corp., and Panasonic Connect. Co.    This is the first time that the system has been installed at a major terminal station in Tokyo. For now, the facial recognition service is available only at a section between Kami-Itabashi Station and Ikebukuro Station on the Tobu Tojo Line. (2026/07/15-19:45)

Enhanced MobileNet with multi-scale feature fusion for automated breast cancer ...

Abstract Accurate and efficient diagnosis of breast cancer from histopathological images remains a major challenge in clinical practice due to subjective interpretation, inter-observer variability, and labor-intensive manual examination. To address these limitations, this work introduces a transfer learning–based framework for automated breast cancer classification using the Breast Cancer Histology Images (BACH) dataset. Several pre-trained deep architectures—including MobileNet, ResNet variants, EfficientNet, and Vision Transformers—were evaluated and extended with a Multi-Scale Feature Fusion (MSFF) module to capture morphological heterogeneity across spatial resolutions. Among these, the Enhanced MobileNet (E‑MobileNet) with MSFF outperforming recent state‑of‑the‑art models and achieving a classification accuracy of 95%, precision of 95%, recall of 94%, and F1‑score of 96%. The framework was further validated on the BreaKHis dataset across multiple magnifications, achieving an average accuracy of 90.6%. These results confirm the robustness and generalization capability of the proposed model for practical clinical deployment in digital pathology. Similar content being viewed by others Introduction Breast cancer remains one of the most significant health challenges facing women globally, with approximately 13.0% of women expected to be diagnosed with the disease during their lifetime. The disease affects over 4 million women currently living with breast cancer in the United States alone, with an annual incidence rate of 130.8 per 100,000 women and a death rate of 19.2 per 100,000 women per year. Despite advances in treatment, breast cancer continues to be the fourth leading cause of cancer death in the United States, with survival outcomes heavily dependent on early detection and intervention as shown in Fig. 1. The critical importance of early detection is underscored by the substantially higher survival rates achieved when breast cancer is identified and treated during its initial stages, making the development of more accurate and efficient detection methods a paramount healthcare priority1. The standard breast cancer diagnostic workflow

Some California grocery stores are using <b>facial recognition</b> to stop shoplifters. Shoppers are divided

Some California grocery stores are using facial recognition to stop shoplifters. Shoppers are divided Jul 15, 2026 10 hrs ago Facebook Twitter WhatsApp LinkedIn SMS Email Print Copy article link Save A trip to the grocery store now comes with a face scan at some Bay Area Grocery Outlet locations. Shoppers say they understand the goal of stopping theft, but not everyone is comfortable with how it works. Facebook Twitter WhatsApp LinkedIn SMS Email Print Copy article link Save ON AIR Currently in Bend 61° Partly Cloudy90° / 58° 12 AM 61° 1 AM 61° 2 AM 59° 3 AM 60° 4 AM 58° Wednesday's PM Forecast- July 15 7 hrs ago Trending Articles Videos ArticlesSorry, there are no recent results for popular articles. VideosSorry, there are no recent results for popular videos. Events

Datasea Intelligent Technology (DTSS) closes share-funded patent deal

UNITED STATES SECURITIES AND EXCHANGE COMMISSION Washington, D.C. 20549 FORM 6-K REPORT OF FOREIGN PRIVATE ISSUER PURSUANT TO RULE 13a-16 OR 15d-16 UNDER THE SECURITIES EXCHANGE ACT OF 1934 For the month of July 2026 Commission File Number: 333-293463 | DATASEA INTELLIGENT TECHNOLOGY LTD. | | (Exact name of registrant as specified in its charter) | Room 302-5, Building C, Gemdale Viseen International Center No.5 Shengfang Road, Daxing District, Beijing, People’s Republic of China 102600 (Address of principal executive offices) Indicate by check mark whether the registrant files or will file annual reports under cover of Form 20-F or Form 40-F. Form 20-F ☒ Form 40-F ☐ Closing of the Patent Acquisition As previously disclosed, Tianjin Information Sea Information Technology Co., Ltd. (“Shuhai Tianjin”), a wholly owned subsidiary of Datasea Intelligent Technology Ltd. (the “Company”), entered into a purchase agreement with Tianjin Qianli Culture Media Co., Ltd. (the “Seller”) to acquire certain patent on June 5, 2026 (the “Purchase Agreement”). Pursuant to the Purchase Agreement, Shuhai Tianjin agreed to pay an aggregate purchase price of RMB 7.0 million. On June 23, 2026, this transaction closed upon the satisfaction of all of the closing conditions set forth in the Purchase Agreement. As consideration for the acquisition, the Company issued an aggregate of 1,122,156 restricted Class A ordinary shares of the Company at a price of US$0.9156 per share, to two individuals designated by the Seller. The Class A ordinary shares issued in this transaction were issued in reliance on the exemption from registration provided by Regulation S under the Securities Act of 1933, as amended, and constitute “restricted securities” within the meaning of Rule 144 under the Securities Act. The Company believes that the acquired patent may potentially complement certain technical capabilities of its Business Execution AI- Agent, including multimodal data

Keep the beard: Improved test photos help <b>facial recognition</b> make a better match

Computer engineers at the University of Wisconsin-Madison have developed a new automated dataset that can help pinpoint why facial recognition fails, helping developers improve the accuracy and reliability of these systems. Facial recognition systems are already a huge part of daily life and are becoming even more common. They safeguard data on our phones, speed us through airport security, and help locate missing persons, among other uses. Despite their prevalence, these systems are still not fail-proof. Change your hair color, grow a goatee, get a sunburn or wear a little extra makeup and these digital gatekeepers might struggle to recognize you. Facial recognition developers are not unaware of these problems; what they struggle with is how to pinpoint, understand and fix the types of changing attributes that cause the systems to fail. That’s why engineers led by Guruprasad Viswanathan Ramesh, a PhD student in electrical and computer engineering, have developed a new automated dataset called CounterFace that can be used to evaluate the performance of facial recognition systems. The UW-Madison team, which also included Kassem Fawaz, an associate professor of electrical and computer engineering, and Ramya Korlakai Vinayak, an assistant professor of electrical and computer engineering, recently presented the project at the ACM Conference on Fairness, Accountability, and Transparency held in Montreal in late June 2026. To evaluate facial recognition systems, developers usually test them on large datasets of human faces from different identities, but these datasets can’t be used to pinpoint identification failures. A less commonly used alternative is a dataset containing pairs of human faces in which one attribute is changed—for instance, images showing someone with and without glasses. Such datasets allow developers to reason why their systems fail. Gathering or producing the huge sample of paired images needed to test the systems, however, is time- and cost-prohibitive.

Gibraltar ushers in a new era as British territory's border fence with Spain is removed

MADRID (AP) — Thousands of people who travel every day between the southern tip of Spain and the British territory of Gibraltar will no longer have to cross a physical border, beginning on Wednesday. The official opening at midnight on Tuesday, after a border fence was removed, allows a new freedom of movement under a historic treaty between the European Union and the United Kingdom. It came after years of post-Brexit wrangling. The contested British overseas territory of 38,000 people is perched at the southern end of the Iberian Peninsula, in a strategic location mere miles from Morocco where the Atlantic Ocean meets the Mediterranean Sea. Soon after midnight, crowds crossed freely between La Línea de Concepción in Spain and Gibraltar in both directions. Many wore Spanish soccer jerseys after Spain’s victory against France in the World Cup semifinal on Tuesday, adding to the celebratory mood. “What you feel here is the brotherhood between the two people,” Gibraltar's Chief Minister Fabian Picardo told Spanish broadcaster RTVE. When Britain left the EU in 2020, the relationship between Gibraltar and the bloc had been left unresolved. Previous talks on a deal to ensure people and goods could keep flowing across the border had made halting progress. In 2025, the EU and U.K. announced an agreement on those issues, with the two sides and Gibraltar’s government signing a treaty Tuesday that eases border crossings. The U.K.’s Foreign Office Minister Stephen Doughty said Tuesday that the agreement secured Gibraltar’s long-term economic future and interests. Maroš Šefčovič, the EU’s trade representative, praised the agreement, too. “It has taken four years of patient, complex negotiation, but the outcome speaks for itself,” Šefčovič said. “It is a very special feeling to see a fence come down.” Without a deal, Gibraltar could have a faced a hard land

RELEASE: To Protect Children, Gottheimer Introduces New Bipartisan Bill Requiring <b>Facial</b> ...

RELEASE: To Protect Children, Gottheimer Introduces New Bipartisan Bill Requiring Facial Recognition Age Verification for Online Sportsbooks Requires Age Checks Before Children Can Bet or Trade Underage 36% of boys aged 11-17 Have Gambled in the Past Year Backed by ParentsRISE and Kalshi Above: Gottheimer introduces legislation to protect children. WASHINGTON, D.C. — Today, Wednesday, July 15, 2026, Congressman Josh Gottheimer (NJ-5), joined by Kalshi CEO Tarek Mansour and additional supporting Members of Congress, introduced the bipartisan “Facial Recognition to Protect Children Act,” new legislation requiring prediction markets and online sportsbooks to use facial recognition technology to verify a user’s age before they can place a bet or trade. Watch Gottheimer’s full remarks here. Last year, American bettors wagered roughly $160 billion on sports, generating about $16 billion in industry revenue — more than Americans spend on movies, books, concerts, and professional sports tickets combined. - Research shows 36 percent of boys ages 11 to 17 have gambled in the past year, a figure that climbs to 40 percent for boys 14 to 17, and more than a quarter of those kids report real consequences, including stress, conflict at home, and problems at school, according to Common Sense Media. - In Iowa, more than 80 reports of underage betting have been sent to the state’s Division of Criminal Investigation. - In Tennessee, sportsbooks flagged more than 400 underage accounts in 2024, up from roughly 100 the year before. It’s not just betting apps, either. A lot of video games today are designed to feel like gambling and hook kids early. Loot boxes, player packs, cosmetics. They train their brains on that same dopamine loop, priming them to bet with real money. Kalshi and ParentsRISE support the bill, and Gottheimer has called on every single sportsbook and prediction market in this

Belgians warned of vulnerability to fake IDs from AI, digital copies | Biometric Update

Belgians warned of vulnerability to fake IDs from AI, digital copies Belgium’s federal police have sounded the alarm about AI-driven identity fraud affecting individuals across the country. The scams described in The Brussels Times are unsophisticated facial portrait swaps within photos of ID documents, which Belgian digital services and public transit ticket inspectors will accept as proof of identity. Federal police told Flemish-language public broadcaster VRT there have been more than 10,000 victims within the past 12 months. Authorities have warned the public that even a poor quality photograph of an ID card can be used to steal data, including the facial photo used in biometric matching by services like online loan applications and ecommerce sites. VRT recounts the difficulties of an individual whose ID card was surreptitiously photographed two years ago. He has received dozens of fines for fare evasion on public transport since, as enforcement officers unquestioningly accept digital copies of his ID presented by perpetrators. Transit operator SNCB-NMBS has begun introducing an ID verification software tool released by Belgium’s government called Checkdoc in response to the situation. In the meanwhile, the report from VRT shows a digital fake ID being accepted by some transit workers, and rejected by another in a part of the system where its frequent fraudulent use has been flagged. The report notes the launch of the country’s actual digital ID later this year could improve the situation by providing a credential that can be digitally verified. Protecting ID document-based verification The frequent cases of unsophisticated ID fraud could be curbed by biometric verifications, but the exposure of ID documents can also fuel another, more sophisticated fraud method. Biometric facial morphing consists of combining two images so that the resulting image matches the biometrics of both individuals, and is one of the most pressing

Is AI better at recognizing faces than you are? Study examines factors that affect accuracy

Newswise — Facial recognition is now a fixture of modern life, powering everything from national border security to the simple convenience of unlocking a smartphone. However, these advancements bring significant risks to privacy, equity and civil rights. While AI can now match faces as accurately as humans, the specific logic these algorithms use to calculate similarity remains a “black box” (closed source). To bridge this gap, new research from the University of Notre Dame compared commercial and open-source AI against the judgment of 4,000 human participants. While humans and AI generally agree on facial similarity, three factors heavily influence accuracy: the race of the participant, the race of the face being viewed and the individual’s natural recognition skill, according to Ahmed Abbasi, the Joe and Jane Giovanini Professor of IT, Analytics and Operations at Notre Dame’s Mendoza College of Business. Abbasi’s research, “The influence of face recognition ability and race on the relationship between psychological and algorithmic similarity,” is forthcoming in the Journal of Applied Research in Memory and Cognition. “Top-tier AI is now as good as the best human experts," noted Abbasi, the director of Notre Dame’s Lucy Family Institute for Data & Society, deputy director of the Data, AI, and Computing Initiative and co-director of the Human-centered Analytics Lab. “If we use AI as the benchmark for ‘good’ recognition, it suggests a large portion of the population is actually not that great at recognizing faces.” This overlap is critical because law enforcement often uses a “human-in-the-loop” system, where an algorithm flags matches and a person makes the final call. “Humans and AI usually see face similarity the same way,” Abbasi said. “However, people who are naturally better at recognizing faces match the AI’s judgments much more closely — at least 15 percent more often, depending on the model.”

Trust Stamp, Seiko Solutions partner on <b>facial recognition</b> service for Japan

Trust Stamp, Seiko Solutions partner on facial recognition service for Japan Seiko Solutions and U.S. digital identity firm TrustStamp are launching a joint project to bring a new facial recognition service to Japan, aiming for a full rollout in fiscal 2026. The companies say they will study system integration and advance real‑world deployment across multiple sectors. The partnership focuses on facial recognition used for admission control at entertainment venues, fraud prevention in financial and payment services, and identity verification for online platforms. Seiko Solutions, based in Chiba, will incorporate TrustStamp’s technology into its authentication center business and help build operational systems for companies adopting the service. The authentication center will act as a shared platform offering facial‑recognition‑based identity verification. Privacy protection is touted as a key feature. Matching will be performed without retaining image data, allowing the companies to offer biometric authentication while limiting the storage of personal information. The technology has already been tested at a live event, where pre‑registered facial data was successfully matched with images captured from attendees during check‑in. The trial confirmed that facial recognition and entry management could operate together smoothly, and development is continuing ahead of the planned nationwide launch. Demand for digital identity verification has grown in Japan as remote and online transactions expand, particularly in financial services governed by strict identity verification rules under the Act on Prevention of Transfer of Criminal Proceeds. Article Topics biometric matching | biometrics | facial recognition | identity verification | Japan | Trust Stamp Comments

Police begin live <b>facial recognition</b> trials in Chester city centre | Local News

Police begin live facial recognition trials in Chester city centre By Dherran Titherington 15th Jul 2026 The first of four planned live facial recognition (LFR) operations has taken place in Chester city centre. Operation Vigilant was carried out on Saturday 11 July with support from neighbourhood officers, the Sexual Offender Management Unit (SOMU), Project Servator officers and Greater Manchester Police's LFR team. Police said the busy city centre provided an opportunity to use the technology to identify people wanted for serious offences and safeguard vulnerable individuals. Officers also spoke with members of the public about how the system works, the privacy safeguards in place and how images are processed. Visitors were invited to watch the technology in use and ask questions. During the operation, officers issued three Community Resolutions for Class A drug possession and seized an illegally used e-bike. Police also said there were no reports of anti-social behaviour within the deployment area. A vulnerable woman was also reunited safely with friends after officers became concerned for her welfare. No arrest was made. A second deployment is planned later this month. Cheshire Police says it is expected to be the first in the UK to use authorised watchlist images from neighbouring police forces, allowing officers to identify wanted people across force boundaries. Detective Chief Inspector Robert Pritchard said: "Our aim under Operation Vigilant is to protect vulnerable people, safeguard those at risk and bring offenders to justice. "The use of Live Facial Recognition technology strengthens our ability to achieve those objectives and helps us prevent harm before it occurs. "This deployment forms part of our ongoing commitment to tackling violence against women and girls and ensuring our communities remain safe places to live, work and visit. "The positive outcomes from this operation demonstrate the value of combining innovative technology

Draconian change coming to major California grocery store chain — and shoppers are furious

Draconian change coming to major California grocery store chain — and shoppers are furious See more of our coverage in your search results. Add The California Post on GoogleA Bay Area grocery chain is bringing in facial recognition technology to try to snare shoplifters — but regular customers are furious. The move is set to be deployed at some Grocery Outlet stores, concerning shoppers their privacy could be infringed upon. The Emeryville-based chain is using software called SAFR, and shoppers will be notified that facial recognition is being used to catch people suspected of shoplifting. One store in Pleasant Hill, in Contra Costa County, will use the technology. California has one of the worst records in the US on shoplifting, as it has skyrocketed 50% since the pandemic. Experienced store manager June Guerrero says she understands why the brand is using facial recognition. “I worked for years as a manager of a store and the theft was just unbelievable,” Guerrero told CBS News. “I agree with it.” Shoppers think privacy and accuracy are their top concerns. “I do understand, but invading my privacy with my picture. I don’t agree on that,” Barbara Jackson told CBS News. “You gotta find a better way.” “It could lead to a lot of problems, I think for companies and businesses and people,” Steve Burdette added. An attorney who is an expert in digital privacy said the technology presumes guilt by scanning every person who enters the store. “This is a dragnet that scans everyone. Even if you’ve done nothing wrong, your face is being scanned,” Mario Trujillo, who works with the Electronic Frontier Foundation, said. “What you’re essentially doing is violating the privacy rights of every customer who walks into your store.” Sign up for the California Morning Report newsletter California's top news, sports