Abstract Identifying changes in satellite images is vital for tasks like tracking land cover and land use, evaluating disaster impacts, and conducting military surveillance. Although conventional techniques for detecting changes in multispectral remote sensing data are commonly applied, they often fail to meet the requirements for reliability and precision. Recently, deep learning methods have emerged, providing more accurate and effective solutions for monitoring environmental transformations and urban expansion in satellite imagery. This paper introduces TransSiamUNet, a deep learning architecture that combines Siamese networks, U-Net segmentation, and Vision Transformers (ViT) for high-precision change detection. The model processes paired Sentinel-2 images via a tailored preprocessing pipeline and integrates local and global feature extraction for pixel-level change segmentation. On the OSCD benchmark, TransSiamUNet achieves an accuracy of 0.94, surpassing the Siamese network (0.86), U-Net (0.84), and Siamese+U-Net hybrid (0.91). These results demonstrate the model’s superior capability in detecting fine-grained urban and environmental changes, highlighting its suitability for real-world remote sensing applications. Data availability Data and code used for training, evaluation, and experimentation in this study are available on request. Code availability The code used for training, evaluation, and experimentation in this study is available on request. Materials availability All datasets and code used in this study are available. The Arabic summarization dataset and model implementations can be available on request. References Richards, J. A. Remote sensing digital image analysis: An introduction (Springer, Cham, 2023a). Liu, X., Zhang, H. & Chen, Y. Urban expansion detection using ndbi and remote sensing data: A case study of rapid urbanization. Remote Sensing 15(4), 1123–1138 (2023a). Hughes, L. H., Schmitt, M., Mou, L., Wang, Y. & Zhu, X. X. Identifying corresponding patches in sar and optical images with a pseudo-siamese cnn. IEEE Geoscience and Remote Sensing Letters 15(5), 784–788 (2018). Daudt, R.C., Le Saux, B. & Boulch, A.
Apr 7, 2026 · via nature.com
Abstract Deep learning has demonstrated remarkable success in augmenting fluorescence imaging under photon-limited conditions. However, existing restoration networks are typically devised for training with augmented patches far smaller than the full-view raw data, an overlooked aspect that compromises fidelity and noise-resistance due to the loss of global statistics. To address this limitation, we propose a large-patch network (LargePNet), which synergizes the large effective receptive field provided by shallow ultra-large-kernel convolutions and the nonlinear representation capabilities of deep networks through scale separation. It effectively and efficiently leverages large-view global information for restoration. Directly trained with large-view images, LargePNet shows contrasting advantages over state-of-the-art small-patch networks, with 0.5-2 dB higher peak signal-to-noise ratio across eight representative restoration tasks, involving implementations for single-image, video, and volumetric fluorescence data. For full-view processing, LargePNet generally holds around 4-fold and 20-fold higher computational efficiency compared to advanced convolution-based and Transformer-based networks, respectively. The assistance of LargePNet helps achieve 30-hour-long fluorescence imaging to monitor cytoskeleton dynamics, and hour-long tri-color super-resolution imaging to investigate organelle interaction, showcasing its advancement in live-cell imaging. Similar content being viewed by others Data availability The open-source data used in this study are all publicly available, as listed in Supplementary Table 15. The self-established dataset of STED denoising/deblurring, virtual sampling of SMLM, volumetric background removal datasets, and the source training data for the open-source BioSR and BioTISR datasets are available: https://zenodo.org/records/15694668. Code availability The source Python code of the LargePNet series, including LargePNet (for single-image restoration), LargeP-GAN (for generative single-image restoration), LargeP-TISR (for time-lapse video restoration), and 3D-LargePNet (for volumetric data restoration) are all publicly available at the GitHub repository56: https://github.com/YiweiHou/LargePNet-for-fluorescence-image-restoration. Trained LargePNet models that can reproduce the results in the paper are available at: https://figshare.com/s/05f576c96b08add7eee0. References Ledig, C. et al. Photo-realistic single image super-resolution using a generative adversarial network. In Proc. IEEE
Apr 7, 2026 · via nature.com
Automates critical DODA processes from document extraction to SAT synchronization for customs agencies, freight forwarders and cross-border carriers navigating Mexico’s 2026 Customs Law Reform. HOUSTON – April 7, 2026 – Freight Technologies, Inc. (Nasdaq: FRGT, “Fr8Tech” or the “Company”), a technology-centric logistics company offering a diversified portfolio of AI software solutions designed to address key inefficiencies in the supply chain, today announced the commercial launch of DODA Smart, an AI-powered platform to automatically verify, monitor, and trace the full lifecycle management of Digital Customs Documents (“DODAs”) for customs agencies, freight forwarders, carriers, and import-exporters operating across the U.S.–México corridor. The platform is designed to synchronize automatically with the México Tax Administration Service (Servicio de Administración Tributaria, or “SAT”) to provide real-time compliance intelligence. Developed by Fr8Tech’s in-house AI Lab, DODA Smart is designed to help customers address new digital recordkeeping and traceability requirements associated with Mexico’s amended 2026 Customs Law Reform. DODA Smart is designed to reduce reliance on physical paper records, manual QR-code reading, fragmented document tracking, and reactive compliance workflows. It is designed to provide automated SAT synchronization and AI-assisted document verification for participants across the customs clearance chain — from the customs agency to the freight forwarder to the carrier. DODA Smart is a natural extension of Fr8Tech’s cross-border intelligence ecosystem and fully integrates with the Company’s existing suite of solutions, completing an essential compliance layer for freight operations across the U.S.–Mexico border. The ability to manage audit-ready customs documentation at scale — quickly, efficiently and accurately — is more important than ever, as cross-border volume grows amid increased nearshoring activity. DODA Smart is a strategic differentiator for any operator moving goods across the border. Javier Selgas, Chief Executive Officer of Freight Technologies, said, “DODA Smart is the next logical step in Fr8Tech’s mission to remove friction
Apr 7, 2026 · via fr8technologies.com
By Ayathandwa Tsili When artificial intelligence (AI) recognises a face, reads a medical scan or makes decisions, it often does so in ways that even its creators say they cannot fully explain. But for Rhodes University MSc Applied Mathematics graduate Georgina Fiorentinos, that wasn’t good enough – so she set out to find out for herself. And she wanted more than a mathematical answer. She wanted to understand how machines interpret the world around them and how reliable those interpretations really are. Her MSc research explored the inner workings of deep learning models, the type of AI behind technologies such as image recognition systems and automated decision-making tools. While these systems are widely used, the processes inside them are often difficult to interpret. “I’ve always been interested in what is happening inside these models,” Fiorentinos explains. “We usually see the input and the output, but the actual process in between can feel like a black box. I wanted to understand how the model decides what information is important and what it ignores.” Her interest began during her Honours research, where she studied how compression techniques could reduce noise in deep convolutional neural networks, models commonly used to analyse images. That work led her to investigate how information changes as it moves through a neural network and whether important details are preserved along the way. Working within the Rhodes University Artificial Intelligence Research Group, and supervised by Professor Atemkeng, she focused on the relationship between ‘signal’ and ‘noise’ inside these systems. In simple terms, signal refers to useful information a model needs to make accurate predictions, while noise refers to irrelevant details that can interfere with those decisions. “An image might seem obvious to us, but to a computer it’s just numbers,” she says. “The model has to learn which patterns
Apr 7, 2026 · via ru.ac.za
This morning, April 7, 2026 (early morning JST), I have released the prototype of UNDEFINED: ILS for free on itch.io — a minimalist puzzle adventure where a local LLM evaluates how players respond to visual incompleteness and contradictions. Players are shown "missing," "contradictory," or "unfinished" visual structures and respond by drawing lines directly on the screen. The AI immediately judges the response with "PROBLEM WAS SOLVED" or "PROBLEM WAS NOT SOLVED" and explains its reasoning in natural language. The way players draw, retry, or skip accumulates as behavioral patterns that influence the game's outcome. This type of interactive experience only became feasible in 2026 due to significant improvements in local LLM image recognition. The prototype includes 10 selected problems out of 100 (ending not yet implemented). I'm releasing it for free to gather wide feedback ahead of the full Steam version. # Key Features Minimalist input: Draw one line — complete gaps, resolve contradictions, redefine rules, or reject the problem. Real-time AI judgment with natural language explanations — it feels like your thinking is being calmly observed. No hints, timers, or limits — the challenge lies in choosing your "attitude" toward ambiguity. Player behavior patterns (not just right/wrong answers) shape the narrative. # Example Problems Complete the unfinished equation "1 + 1 =" or leave it as is? Fill a missing face, highlight the gap, or reinterpret the pattern entirely? In a blocked road scenario, draw a path, change the rules, or reject the premise? # Specs Title : UNDEFINED: ILS Genre : Puzzle Adventure / Single Player Planned Release Date : Autumn 2026 Languages : English, Japanese, Chinese（Simplified / Traditional), Korean Download the Free Prototype (Available Now) : https://kamekichi.itch.io/undefined-ils Steam Store Page : https://store.steampowered.com/app/4481900 Play Demo Movie : https://youtu.be/VQGQtjyYXv4 System Requirements : Windows 10/11 – VRAM 6GB+ GPU recommended
Apr 7, 2026 · via gamespress.com
Tokyo – April 7, 2026 – TOPPAN Holdings Inc. (TYO: 7911) (TOPPAN Holdings) and subsidiary TOPPAN Inc. (TOPPAN) have developed an AI-Optical Character Recognition (OCR) engine that can decipher medieval Greek, a type of writing that is generally difficult to understand. Moving forward, thanks to a collaborative relationship with the Vatican Apostolic Library (Vatican Library), the Printing Museum, Tokyo (operated by TOPPAN Holdings) plans to scan images and digitized text from Greek manuscripts belonging to the Vatican Library. These will be used as learning data to refine accuracy, with the goal of increasing TOPPAN’s AI-OCR recognition accuracy to more than 95%. Visuals showing the findings of this approach will be displayed during the “How Masterpieces Are Born: Biblioteca Apostolica Vaticana â ¢+” special exhibition running from April 25, 2026, at the Printing Museum, Tokyo. TOPPANâs AI-OCR Engine Development Old texts hold a myriad of information regarding important historical facts and regional culture. However, many such texts are handwritten and are difficult to read for most people in the modern world. Correctly interpreting these texts to preserve culture is now an important challenge not only in Japan, but also on the global stage. For the past 30 years or so, the TOPPAN Group has been collaborating with the Vatican Library on several projects to safeguard culture for future generations. During that time the Vatican Library has released over two million items from part of its collection to the public for research and educational purposes in the form of IIIF1 high-resolution images. A total of nine million images were released, and that number continues to grow. Additional information such as transcriptions2 and annotations has been added to some of the Greek manuscripts, but experts in medieval Greek would need to work for a long period of time to complete the entire collection.
Apr 7, 2026 · via holdings.toppan.com
Chinese spy cameras remain in widespread use in the United States, in Canada and Mexico and worldwide. They are sold as security and traffic cameras, but that is a cover story for their real use. Such cameras are used for social and political control turning countries into digital prisons. The US and Israel have been able to hack them. In places where they are banned, China is now using drones to conduct spying in place of fixed installation cameras. The recent persistent Barksdale Air Base drone incursion along with many others may be China’s partial answer to the ban on its security cameras. In fact, the rise of drone security incidents corresponds almost exactly to the US 2019 ban on Chinese cameras at American military bases. What is happening in the United States is taking place elsewhere. Back in 2018 I discovered a sole source contract for Hikvision cameras for the US Embassy in Kabul, Afghanistan. Hikvision is Hangzhou Hikvision Digital Technology Co., Ltd. It is a publicly traded company, but it is effectively controlled by the Chinese government. While it is listed on the Shenzhen Stock Exchange (SZSE: 002415), its ownership structure is a mix of state-owned enterprises (SOEs), private founders, and institutional investors where state-owned enterprises control more than half the company. Why, I wondered, was the US Embassy in Kabul ordering Chinese cameras for its security, and why was the contract sole-source, meaning no other camera would qualify for the job? As I began asking questions about the announced contract (a sole source announcement means the deal is done), I found out that Hikvision, along with another Chinese camera company, Dahua Technology (Zhejiang Dahua Technology Co., Ltd.), apparently had weak security amounting to a functional back door. These cameras work through the Internet and can be easily
Apr 7, 2026 · via asiatimes.com
Netflix is making a bigger play for young viewers with the launch of a games app for kids, the renewal of two preschool shows and a new series based on one of the most enduring nursery rhymes of all time. The streamer on Monday launched Netflix Playground, a gaming app aimed at kids 8 and under that features activities with characters from Peppa Pig, Sesame Street, Storybots and other kids’ shows in Netflix’s library. The app is free for all subscribers and promises no in-game purchases or other fees and no advertising (regardless of whether the linked account subscribes to Netflix’s ad-supported tier). Related Stories Games will also be playable offline, should parents not want to burn their wireless hotspot on a long car ride. The Playground app launched Monday in the United States, Canada, U.K., Australia, the Philippines and New Zealand and will debut in the rest of the world on April 28. Along with Playground’s launch, Netflix on Monday ordered an animated preschool series called Young MacDonald. Created by Gabrielle Meyer (Ada Twist, Scientist), the show centers on Mac, the grandson of Old MacDonald who cares for his farm animals and crops with the help of a pig named Dumpling. The streamer has also ordered new seasons of animated shows Trash Truck and The Creature Cases. “We’re building a world where kids can not only watch their favorite stories, they can step inside them and interact with their favorite characters,” said John Derderian, vp animation series and kids & family TV at Netflix. “We’re creating a seamless destination for discovery, learning, and play. Whether it’s reuniting with Hank and the Trash Truck crew for new adventures or making a smoothie with Peppa Pig, watching and playing on Netflix can be the fun and easiest part of every family’s
Apr 6, 2026 · via hollywoodreporter.com
Netflix has released a new iPhone and iPad app called Netflix Playground. Similar to Apple Arcade, the new Netflix Playground app includes ad-free games with no in-app purchase content. Netflix Playground includes 7 ‘mini games’ for younger kids Netflix Playground includes multiple “mini games” that younger kids will enjoy. These include content from Peppa Pig, Sesame Street, Dr. Seuss, and more. At launch, Netflix Playground includes seven mini games inside the new app: - Dr. Seuss’s Red Fish, Blue Fish: Dive into musical play zones filled with rhythmic fun and gentle surprises. - Dr. Seuss’s Horton!: Welcome to the jungle! Horton’s got fun and games that encourage creativity through interactive cause-and-effect play. - Bad Dinosaurs: Prehistoric puzzles, sticker scenes, music, and memory games abound with Janet and her brood of tiny thunderlizards. - Sesame Street: It’s always a sunny day on Sesame Street, and the activities here encourage pattern recognition, object recognition, and free-form play. - Dr. Seuss’s The Sneetches: Your kids will join Stella Sneetch on an imaginative adventure through Starbelly and Moonbelly Villages via creative play activities like the Shape Printer and Vehicle Builder, which encourage imaginative design and pattern recognition. - Peppa Pig: Play, count, care for guinea pigs, decorate cakes, and a whole lot more with Peppa and the rest of her Peppatown crew. - StoryBots: These inquisitive creatures are here to help your kids hone their memory, improve pattern recognition, develop budding musical skills, and more. More titles will be added throughout the year, Netflix says, including content from “Gabby’s Dollhouse, KPop Demon Hunters, PJ Masks, My Little Pony, and PAW Patrol.” The company says Netflix Playground access is part of every membership, not just ad-free and premium tiers. Each mini game can be downloaded individually within Netflix Playground. Once downloaded, mini games are available
Apr 6, 2026 · via 9to5mac.com
Abstract Road crack detection is crucial for road maintenance and traffic safety. To address the low efficiency and limited generalization capability of traditional crack detection methods, this research proposes an improved model dubbed EVA-YOLOv8 (Efficient ViT Attention-YOLOv8) based on the YOLOv8n framework. This model integrates MobileViT Block and an Efficient Multi-scale Attention (EMA) mechanism, while employing the more efficient GhostConv to provide lightweight optimization for the network. Comparisons and ablation experiments were conducted on road crack datasets, and the attention mechanism of the model on crack features was analyzed using Grad CAM + + heatmap. Results indicate: (1) The EVA-YOLOv8 model achieved values of 0.897 (mAP@0.5), 0.706 (mAP@0.5:0.95), 0.907 (Precision), 0.881 (Recall), and 0.894 (F1-score), exhibiting good generalization ability across multiple categories, different scales, and low-contrast scenarios. (2) Compared with the original YOLOv8, the improved model demonstrates enhanced performance: mAP@0.5 and Recall are increased by 6.6% and 5.3%, respectively, while the parameters are reduced by 16.3%. (3) Grad-CAM + + heatmaps indicate that the model not only achieves high response values in the main region of the target but also performs well in target boundary localization and background suppression. This research may provide a reference for related fields. Data availability Data are available from the corresponding author upon reasonable request. References Tian, Z., Shao, X. & Bai, Y. Graph-MambaRoadDet: A Symmetry-Aware Dynamic Graph Framework for Road Damage Detection. Symmetry 17, 1654 (2025). Ma, L. & Chen, M. Road damage detection based on improved YOLO algorithm. Sci. Rep. 15, 28506 (2025). Wang, J. et al. Road defect detection based on improved YOLOv8s model. Sci. Rep. 14, 16758 (2024). Xing, Y. et al. EMG-YOLO: road crack detection algorithm for edge computing devices. Front. Neurorobotics. 18, 181423738–181423738 (2024). Cano-Ortiz, S. et al. Leveraging a deep learning generative model to enhance recognition of minor
Apr 6, 2026 · via nature.com
On 1 June 2025, China’s Cyberspace Administration (CAC) brought into force the Measures for the Security Management of Face Recognition Technology Applications (the „Measures“). This landmark regulation is the first piece of dedicated legislation in China governing the use of biometric facial data, and it carries significant implications for any organization processing face recognition data within Chinese territory. Why Now? China already had a general legal framework in place. The Personal Information Protection Law (PIPL), the Data Security Law, the Cybersecurity Law, and the Network Data Security Regulations all touch on how personal and sensitive data should be handled. The Measures build directly on these, filling a gap with rules specifically designed for face recognition. Face recognition technology has quietly become part of everyday life in China. Airports and train stations use it for identity checks. Residential compounds and office buildings rely on it for access control. Banks and payment platforms deploy it to authenticate transactions. Public security agencies use it to track and identify suspects. All of this has brought real convenience. But it has also raised serious concerns. Unlike a password, facial data cannot be reset once it is leaked. The growing risk of identity fraud, unauthorized profiling, and covert surveillance eventually pushed regulators to act. Who Does This Apply To? According to Article 2 of the Measures, the regulation covers any entity or individual applying face recognition technology to process facial information within mainland China. There is one notable exception. Organizations doing research and development or algorithm training with facial data are not covered by the Measures, though they still have to comply with PIPL and other relevant laws. That said, once the technology moves from the lab into a real-world application, full compliance obligations apply. The Core Compliance Requirements - Mandatory Disclosure (Article 5): Before collecting
Apr 6, 2026 · via datenschutz-notizen.de
Abstract Automated skin lesion detection is essential for early dermatological diagnosis. Most deep learning algorithms employ dermoscopic images and ignore the clinical context of dermatologists. This constraint decreases the robustness and interpretability, particularly in visually ambiguous instances. An explainable multimodal cross attention framework that merges clinical text with dermoscopic images to increase diagnostic accuracy and semantic grounding in automated skin lesion detection. A Text-Guided Cross-Attentive Visual Feature Network multimodal learning architecture (TG-CAVNet) using Bio-ClinicalBERT based clinical text encoding and EfficientNet-B4 visual feature extraction is proposed. The framework uses text-guided channel-wise feature modulation, text-queried cross-attention for semantic-spatial alignment and adaptive multi-stream fusion to merge complementary representations. The model was trained end-to-end using hybrid focal and cross-entropy losses. On a multimodal dermoscopic dataset of 6194 aligned image-text samples, TG-CAVNet outperforms state-of-the-art multimodal baselines with 90.75% accuracy and a macro Jaccard score of 0.82. Ablation investigations are performed that confirmed the separate and synergistic impacts of the components, whereas attention visualizations improved interpretability. Text-guided cross-attentive multimodal learning improves the performance and explainability of automated skin lesion identification. The robust and clinically interpretable decision-support framework TG-CAVNet demonstrates the necessity of integrating semantic clinical context with visual analysis in dermatological AI systems. Similar content being viewed by others Data availability Dataset is available at the link. https://ieee-dataport.org/documents/multimodal-dermoscopic-dataset. References Debelee, T. G. Skin lesion classification and detection using machine learning techniques: A systematic review. Diagnostics. 13(19), 3147. https://doi.org/10.3390/diagnostics13193147 (2023). Naqvi, M., Gilani, S. Q., Syed, T., Marques, O. & Kim, H. C. Skin cancer detection using deep learning—A review. Diagnostics. 13(11), 1911. https://doi.org/10.3390/diagnostics13111911 (2023). Vieira, J., Mendonça, F. & Morgado-Dias, F. Deep learning approaches for skin lesion detection. Electron 14, 2785. https://doi.org/10.3390/electronics14142785 (2025). Haggenmüller, S. et al. Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts. Eur. J. Cancer. 156, 202–216.
Apr 6, 2026 · via nature.com
Facial recognition drones to be deployed in the Channel to catch migrant smugglers steering small boats Facial recognition drones are to be deployed in the Channel to catch migrant smugglers driving the small boats. Military-grade cameras that can identify faces up to half a mile away are now being trialed by Border Force. The radar-enabled technology will be able to spot targets even if they have altered their outfit or appearance. Officers have reported that those piloting the boats change their clothes when they see British rescue vessels to blend in with passengers, or even shave at sea to make them more difficult to recognise. Thus far, this has allowed many to avoid being caught. The Home Office hopes the new strategy, first reported by The Times, will increase the number of prosecutions. Smugglers can be convicted of assisting unlawful immigration - an offence that can carry a sentence of life imprisonment. But the technology must undergo rigorous testing and review in order to overcome practical and legal hurdles before being rolled out. It comes after Shabana Mahmood signed a two-month extension deal for French cops to stop small boats Dangerous crossings in the Channel have increased over the past three years, with 41,472 people arriving in the UK by small boat in 2025 The facial-recognition drones are the latest initiative from the Home Office in its battle to drive down the number of crossings. So far this year, 4,766 migrants have made the journey across the channel, which is down 28 percent on the same period last year. Last week, two people died and three were injured when hundreds of migrants tried to pile onto a rubber dinghy bound for Dover from France's shore. Smugglers took advantage of the improved weather in northern France to launch at least five
Apr 6, 2026 · via dailymail.co.uk
4chan won’t play by UK age check rules, raising question about enforcement potency If the UK doesn’t like how 4chan operates, it can shut the site down. That’s the gist of the message from the online message board best known for being an incubator for misogyny, in response to demands from UK regulator Ofcom that the site fall in line with the UK’s Online Safety Act (OSA), and pay for violations. In keeping with its generally adversarial stance, 4chan says it won’t follow Ofcom’s rules because “the United Kingdom lost the American Revolutionary War,” and as such UK speech law doesn’t apply to companies based in the U.S. In a letter from its lawyer, Preston Byrne, the firm says it “reserves all rights and waives none,” and punctuates the statement with an image of giant cartoon hamster Nigel J. Whiskerford dressed as Godzilla – per Byrne’s explanation on X, “a private international law service of process joke.” “I told Ofcom in Oct that their letters, which were not properly served, would be shredded for my pet hamster’s enclosure,” Byrne writes. From the beginning, 4chan has treated Ofcom’s demands as a joke. Ofcom has continued to prosecute 4chan, issuing a fine of £450,000 (about $596,000) to the site for “not having age checks in place to prevent children from seeing pornography on its site,” and an extra £70,000 (about $92,000) for not doing a risk assessment and not being complete enough in its terms of service. More fines are coming. But 4chan’s response raises the question: what good is enforcement if foreign companies simply ignore it? Debate over where responsibility for online content lives The question is primarily one of jurisdiction. In the U.S., the First Amendment reigns as holy writ, and American companies are happy to leverage it for their
Apr 6, 2026 · via biometricupdate.com
Facial recognition software will be deployed on drones in the Channel to help prosecute people smugglers steering migrant boats bound for Britain under Home Office plans, The Times can reveal. Border Force is trialling military-grade, radar-enabled cameras that will be able to identify an individual up to half a mile away, regardless of whether they have changed their outfit or appearance. Border Force officers have reported pilots of the migrant dinghies who change their outfits after they see a British rescue boat approaching to blend in with the other passengers. The boat pilots have even been seen shaving, so they cannot be identified as responsible for facilitating the journey, according to Border Force sources. This enabled them to evade prosecution for assisting unlawful immigration, an offence that can carry a sentence of life imprisonment. The Home Office hopes that using the precision technology will help boost the number of people smugglers who are prosecuted. However, the technology requires extensive trials and testing in order to overcome practical, legal and ethical challenges. The measure is the latest initiative being pursued by the Home Office to target the criminal gangs facilitating the crossings. A total of 4,766 migrants have crossed so far this year, which is down 28 per cent compared with the same period last year. Last week, two people died after a dinghy carrying about 50 migrants got into serious difficulty shortly after leaving Gravelines beach in northern France. There are fears that the failure to renew a deal to pay for French beach patrols could lead to a surge in crossings this summer. Shabana Mahmood, the home secretary, agreed last week to extend the present deal by two months until the end of May, after Britain and France failed to reach an agreement on a new three-year deal. Talks
Apr 6, 2026 · via thetimes.com
First implemented in October 2023, the facial recognition scanners haven’t been a main point of entry for Universal Islands of Adventure recently. But we noticed that they have returned. Facial Recognition For Entry During a visit on April 5, we noticed the facial recognition devices were available again at Universal Islands of Adventure. The machines are still often used for the passholder line, but haven’t been available for non-passholder ticket entry for some time—potentially even since 2025. Photo recognition entry is not required, and guests may opt out of it. The facial recognition machines for the non-passholder ticket entry were not in use this past weekend either. This technology is not currently in use at Universal Studios Florida, which implemented it about a month after Universal Islands of Adventure in November 2023. Facial recognition cameras were later installed in 2024 at express lanes throughout Universal Studios Florida. Here is the updated information about photo validation/facial scanning from Universal Orlando’s Privacy Info Center. As a note, although this webpage appears to be current and on the site, it still refers to the photo recognition “technical rehearsal period” which took place a few years ago. What is Photo Validation? Photo Validation is a faster and more seamless way for our Guests to access select experiences throughout Universal Orlando Resort during their visit. How is Photo Validation being used at Universal Orlando? We use Photo Validation to verify tickets and ticket holders – making it a faster and more seamless way for our guests to access select experiences during their visit. Photo Validation is currently used at the park entrances of Universal Islands of Adventure, Universal Studios Florida, and Universal Volcano Bay. Now, Guests may also use Photo Validation to verify and use their Universal Express Pass at select attractions throughout Universal Islands
Apr 6, 2026 · via wdwnt.com
On July 14, Tennessee grandmother Angela Lippswas arrested and spent more than five months in jail for a crime in North Dakota she did not commit. Her wrongful arrest stemmed from an AI facial recognition match, despite evidence showing she was not the person who committed the crime and had never even visited the state. Unfortunately, her story is not unique. Wrongful arrests tied to technology are happening across the country. Robert Dillon, from Lee County, Florida, was arrested on a warrant out of Jacksonville—hundreds of miles away—accused of luring or enticing a child. Facial recognition technology had produced a 93% match to his photo. His image was even placed in a photo lineup for a witness two months later, who then identified him. But beyond the tech-generated match and the lineup, no evidence connected Dillon to the crime. His charges were eventually dropped and his record cleared, but not before his life was upended. In another case in Orlando, Florida, a man was accused of fraud and theft tied to a hotel stay. The initial encounter was captured on body camera footage when the suspect was issued a trespass warning. Law enforcement believed the man gave a false identity, leading officers in another county to arrest Beau Burgess on those charges. Burgess repeatedly insisted he was innocent and provided a timecard proving he was at work—70 miles away—when the incident occurred. When a local news outlet requested body camera footage and followed up with the Orlando Police Department, officials initially denied that facial recognition had been used. However, a later internal investigation revealed officers had used the FACES program, relying on a decades-old mugshot and placing Burgess in a photo lineup. A hotel employee then identified him. Ultimately, the state attorney dropped the case. Orlando Police Department’s Policy on
Apr 6, 2026 · via rightoncrime.com
In recent city council meetings in Dunwoody, Georgia, a spokesman for Flock Safety, a Georgia-based firm that provides automated license plate readers, has found himself in the hot seat again. For two months running, some residents of the affluent north Atlanta suburb in the region’s tech corridor have been demanding an end to the city’s contract with the security firm, which has drawn similar protest from California to New York. Between a recent change in terms of service that removed a line assuring customers that the company does not own and will not sell customer data – done to eliminate redundancy, Flock says – and videos circulating of hackers showing how they had obtained access to live video feeds from Flock cameras, Dunwoody residents and some members of the city council have been in in revolt. “When you hear from our police department saying they trust Flock, it’s clear that our police are too lazy to verify what a vendor such as Flock says,” said Joe Hirsh, a Dunwoody resident, haranguing the council over privacy breaches last week. “You and I both know the next time Flock is misused in our city, you will turn a blind eye because none of you are trustworthy with our records.” Kerry McCormack, Flock Group Inc’s public relations manager for the east coast, spent about half an hour explaining that the company doesn’t own the images its increasingly ubiquitous license plate reader cameras take, and that it doesn’t sell the data. “One hundred per cent of data, which is the photo of the public license plate, is owned by our customers,” McCormack said. “So, you own that data. It is never sold. We don’t have that in our model. It is written into your contract. We do not sell data.” Skepticism of these statements
Apr 6, 2026 · via theguardian.com
In a decisive move to combat rising digital fraud, the Reserve Bank of India (RBI) is evaluating the deployment of facial recognition technology across ATMs, bank branches, and service counters. The initiative signals a shift toward AI-driven identity verification to strengthen trust in India’s rapidly expanding digital banking ecosystem. The proposed system would act as an additional security layer, enabling real-time identity authentication. By verifying customers through facial biometrics, banks can significantly reduce unauthorized transactions and identity fraud, which have grown more sophisticated in recent years. Experts highlight that cybercriminals increasingly exploit social engineering and digital manipulation to bypass traditional controls. AI-powered facial recognition can help detect anomalies instantly, flag suspicious behavior, and trigger preventive actions before financial damage occurs. To assess feasibility, the RBI has asked both public and private sector banks to submit feedback by month-end. The inputs will cover cost implications, technical readiness, and operational challenges, helping regulators determine the pace and scale of implementation. However, the rollout is not without hurdles. Banks will need to invest in high-quality cameras, biometric systems, and seamless integration with existing ATM and core banking infrastructure, which could be expensive—especially for smaller institutions. Alongside this, the RBI has proposed stricter compensation norms for digital fraud victims. The draft suggests up to 85% compensation for smaller frauds, capped at ₹25,000, reinforcing accountability while encouraging stronger preventive frameworks. As digital transactions surge, security remains the biggest concern. Facial recognition could redefine banking safety, but its success will depend on balancing innovation with privacy, compliance, and robust governance. See What’s Next in Tech With the Fast Forward Newsletter Tweets From @varindiamag Nothing to see here - yet When they Tweet, their Tweets will show up here.
Apr 6, 2026 · via varindia.com
Abstract The increasing use of medical imaging in healthcare settings presents a significant challenge due to the additional workload for radiologists, yet it also offers opportunity for enhancing healthcare outcomes if effectively leveraged. Artificial Intelligence (AI)-based 3D medical image retrieval holds the potential to alleviate radiologists’ burden by offering evidence-based diagnostics and predictions that can enhance the scale and accuracy of radiologists, while simultaneously supporting output verification for safety and regulatory compliance. Despite its promise, the field of 3D medical image retrieval lacks established evaluation benchmarks, comprehensive datasets, and rigorous evaluation studies. This paper aims to address these gaps by introducing the first benchmark for 3D Medical Image Retrieval (3D-MIR) and evaluating various pre-trained models and implementation approaches for retrieval. The benchmark includes four anatomies (Liver, Colon, Pancreas, and Lung) imaged using computed tomography (CT). A range of 3D image search strategies are explored, including those that use aggregated 2D slices/3D volumes (Image-to-Image) and text embeddings from popular foundation models as queries (Text-to-Image). Additionally, novel multi-modal and supervised fine-tuning approaches are investigated to generate multi-modal embeddings for 3D image retrieval. The paper provides quantitative and qualitative assessments of each approach, along with an in-depth discussion offering insights for future research and solutions to support clinical decision-making and healthcare applications. To foster advancement in this field, our benchmark, models, and code are made publicly available. Data availability The code and datasets generated and analyzed during the current study are available in this repository: https://github.com/abachaa/3D-MIR. References Harry, E. et al. Physician task load and the risk of burnout among us physicians in a national survey. Jt. Comm. J. Qual. Patient Saf. 47, 76–85 (2021). Wang, D. et al. Medfmc: A real-world dataset and benchmark for foundation model adaptation in medical image classification. arXiv preprint arXiv:2306.09579 (2023). Yang, J., Shi, R. & Ni,
Apr 6, 2026 · via nature.com