A facial recognition system deployed by the Metropolitan police at Oxford Circus on 13 May in London. A facial recognition system deployed by the Metropolitan police at Oxford Circus on 13 May in London. 'Urgent clarity' sought over racial bias in UK police facial recognition technology The UK's data protection watchdog has asked the Home Office for "urgent clarity" over racial bias in police facial recognition technology before considering its next steps. The Home Office has admitted that the technology was "more likely to incorrectly include some demographic groups in its search results", after testing by the National Physical Laboratory (NPL) of its application within the police national database. The report revealed that the technology, which is intended to be used to catch serious offenders, is more likely to incorrectly match black and Asian people than their white counterparts.

Facial recognition technology could be used more often by UK police forces, according to new plans announced by the Home Office. Policing and crime minister Sarah Jones said a widespread rollout of the equipment could mark the biggest breakthrough in catching criminals since DNA matching. People are being asked for their views on its use, as part of a 10-week consultation launched on Thursday, possibly paving the way for new laws. Jones credited the technology for helping to arrest thousands of criminals, but campaign group Big Brother Watch said increased use would make George Orwell roll in his grave. Facial recognition is used to locate wanted suspects and find vulnerable people.

When Face Recognition Doesn't Know Your Face Is a Face An estimated 100 million people live with facial differences. As face recognition tech becomes widespread, some say they're getting blocked from accessing essential systems and services. Autumn Gardiner thought updating her driving license would be straightforward. After getting married last year, she headed to the local Department of Motor Vehicles office in Connecticut to get her name changed on her license. While she was there, Gardiner recalls, officials said she needed to update her photo.

'What we have seen from Croydon is that it works,' said Sarah Jones. 'What we have seen from Croydon is that it works,' said Sarah Jones. Policing minister says government will'put some parameters' around its deployment in England Labour plans to consult on the use of live facial recognition (LFR) technology before expanding it across England, the new policing minister has told the party's annual conference. Sarah Jones, a Home Office minister, said the government would "put some parameters" over when and where it could be used in future. Campaigners claim the police have been allowed to self-regulate their use of the technology because of the lack of a legal framework and deploy the technology's algorithm at lower settings that are biased against ethnic minorities and women.

WIRED published a shocking investigation this week based on records, including audio recordings, of hundreds of emergency calls from United States Immigration and Customs Enforcement (ICE) detention centers. The calls--which include reports of incidents of staff sexual assaults, suicide attempts, and head injuries--indicate a system inundated by life-threatening incidents, delayed treatment, and overcrowding. In a 6-3 decision on Friday, the US Supreme Court upheld a Texas porn ID law, finding that age verification for explicit sites is constitutional. In a dissent, Justice Elena Kagan warned that this determination ignores First Amendment precedent and will have privacy implications for adults. Looking at the US bombing of Iranian nuclear sites last weekend, President Donald Trump posted initial announcements of the strikes on the social Network Truth Social, which then began suffering intermittent outages.

Facial recognition technology has made significant advances, yet its effectiveness across diverse ethnic backgrounds, particularly in specific Indian demographics, is less explored. This paper presents a detailed evaluation of both traditional and deep learning-based facial recognition models using the established LFW dataset and our newly developed IITJ Faces of Academia Dataset (JFAD), which comprises images of students from IIT Jodhpur. This unique dataset is designed to reflect the ethnic diversity of India, providing a critical test bed for assessing model performance in a focused academic environment. We analyze models ranging from holistic approaches like Eigenfaces and SIFT to advanced hybrid models that integrate CNNs with Gabor filters, Laplacian transforms, and segmentation techniques. Our findings reveal significant insights into the models' ability to adapt to the ethnic variability within Indian demographics and suggest modifications to enhance accuracy and inclusivity in real-world applications. The JFAD not only serves as a valuable resource for further research but also highlights the need for developing facial recognition systems that perform equitably across diverse populations.

Meta is fighting the scourge of celebrity investment scam ads with facial recognition technology to detect those who most often have their images used. The parent company of Facebook and Instagram announced on Monday it would begin trialling the use of facial recognition technology with a select pool of 50,000 celebrities or public figures worldwide on an opt-out basis in December. If Meta's existing systems suspect an ad may be a scam, it would compare the images in the ad against the public figure's Facebook and Instagram profile pictures, and if it's a match and the ad is a scam, it will be deleted. "This process is done in real time and is faster and much more accurate than manual human reviews, so it allows us to apply our enforcement policies more quickly and to protect people on our apps from scams and celebrities," David Agranovich, director of global threat disruption at Meta, told reporters on Monday. The celebrities must have a Facebook or Instagram profile in order to participate in the system.

In recent years robots have become an important part of our day-to-day lives with various applications. Human-robot interaction creates a positive impact in the field of robotics to interact and communicate with the robots. Gesture recognition techniques combined with machine learning algorithms have shown remarkable progress in recent years, particularly in human-robot interaction (HRI). This paper comprehensively reviews the latest advancements in gesture recognition methods and their integration with machine learning approaches to enhance HRI. Furthermore, this paper represents the vision-based gesture recognition for safe and reliable human-robot-interaction with a depth-sensing system, analyses the role of machine learning algorithms such as deep learning, reinforcement learning, and transfer learning in improving the accuracy and robustness of gesture recognition systems for effective communication between humans and robots.

The proposed model aims to develop a speech recognition technology for hearing, speech, or cognitively disabled people. All the available technology in the field of speech recognition doesn't come with an interface for communication for people with hearing, speech, or cognitive disabilities. The proposed model proposes the speech from the user, is transmitted to the speech recognition layer where it is converted into text and then that text is then transmitted to the morse code conversion layer where the morse code of the corresponding speech is given as the output. The accuracy of the model is completely dependent on speech recognition, as the morse code conversion is a process. The model is tested with recorded audio files with different parameters. The proposed model's WER and accuracy are both determined to be 10.18% and 89.82%, respectively.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. The city of Detroit will pay 300,000 to a man wrongly accused of shoplifting. Robert Williams' driver's license picture was incorrectly flagged as a likely match for a man captured on grainy security video at a Shinola watch store theft in 2018. Williams was arrested two years later in front of his wife and two young daughters on their front lawn in the Detroit suburb of Farmington Hills.