"What exactly is computer vision then? Computer vision is a research field working to equip computers with the ability to process and understand visual data, as sighted humans can. Human brains process the gigabytes of data passing through our eyes every second and translate that data into sight - that is, into discrete objects and entities we can recognise or understand. Similarly, computer vision aims to give computers the ability to understand what they are seeing, and act intelligently on that knowledge."
– Computer vision: Cheat Sheet. ZDNet.com (December 6, 2011), by Natasha Lomas.
Amazon's controversial facial recognition technology has incorrectly matched more than 100 photos of politicians in the UK and US to police mugshots, new tests have revealed. Amazon Rekognition uses artificial intelligence software to identify individuals from their facial structure. Customers include law enforcement and US government agencies like Immigration and Custome Enforcement (ICE). It is not the first time the software's accuracy has been called into question. In July 2018, the American Civil Liberties Union (ACLU) found 28 false matches between US Congress members and pictures of people arrested for a crime.
Russian researchers from HSE University and Open University for the Humanities and Economics have demonstrated that artificial intelligence is able to infer people's personality from'selfie' photographs better than human raters do. Conscientiousness emerged to be more easily recognizable than the other four traits. Personality predictions based on female faces appeared to be more reliable than those for male faces. The technology can be used to find the'best matches' in customer service, dating or online tutoring. The article, "Assessing the Big Five personality traits using real-life static facial images," will be published on May 22 in Scientific Reports.
The American Civil Liberties Union (ACLU) is taking Clearview AI to court, claiming the company's facial surveillance activities violate the Illinois Biometric Information Privacy Act (BIPA) and "represent an unprecedented threat to our security and safety". The legal action, brought on by lawyers at the ACLU of Illinois and the law firm Edelson PC, is on behalf of organisations that represent survivors of sexual assault and domestic violence, undocumented immigrants, and other vulnerable communities. Clearview AI, founded by Australian entrepreneur Hoan Ton-That, provides facial recognition software, marketed primarily at law enforcement. The ACLU said not stopping Clearview AI would "end privacy as we know it". "Face recognition technology offers a surveillance capability unlike any other technology in the past. It makes it dangerously easy to identify and track us at protests, AA meetings, counselling sessions, political rallies, religious gatherings, and more," the ACLU wrote in a blog post.
Artificial intelligence is the next big military advantage. For example, in early 2019, the U.S. announced a strategy for harnessing AI in many parts of the military including. Intelligence analysis, decision-making, vehicle autonomy, logistics, and weaponry, reports Technology Review. In fact, according to the U.S. Army, "The AI market was more than $21 billion in 2018, and it is expected to grow almost nine times larger by 2025. AI systems provide predictive analysis to interpret human inputs, determine what we most likely want, and then provide us with highly relevant information."
Lorex is an old hand at building security cameras, and now it's moving into the smart home market, with its 1080p Wi-Fi Video Doorbell (model number LNWDB1) being the first product to reach the market. With a $130 asking price, this device is clearly aimed at the budget end of the spectrum. It doesn't have much in the way of bells and whistles, but it does have onboard storage that eliminates the need for a subscription to store video clips in the cloud, and it performed reliably enough during my review. But this is a crowded market, and you'll encounter several competitors that deliver more, including at least one that operates on battery power (Lorex's device relies on low-voltage wiring). Lorex anticipates you'll be replacing an existing wired doorbell that's mounted on a flat wall (there are no wedge options for installation on slanted surfaces or to otherwise change the camera's viewing angle), and I found the installation process to be straightforward and as expected.
If you own an iPhone X or later and have gone out into the world recently, you probably noticed an unfortunate side effect of the new mask-wearing culture: Face ID doesn't work. It is more of a feature than a bug, but the fact of the matter is that if Apple's True Depth camera system can't scan your whole face, it won't unlock your phone. If you're wearing a mask like most stores and restaurants require, you're left typing in your passcode whenever you want to check your shopping list or pay your bill. Apple offered up a workaround with the recent iOS 13.5 update, but it's hardly a fix. Now, instead of waiting for Face ID to fail a couple times before the passcode screen pops up, you can swipe up from the bottom of the screen to quickly enter your code.
"This is a bill being sold as a privacy bill, but it's a wolf in sheep's clothing," Matt Cagle, an attorney for the American Civil Liberties Union of Northern California, said in an interview. The ACLU, Electronic Frontier Foundation and other civil liberties groups held a virtual rally Thursday night to rail against the bill, calling it vaguely worded and potentially dangerous for low-income communities hit hard by the coronavirus. Their remarks were the latest shots fired from a campaign to halt the legislation. The bill's fate in California--which has pushed for more aggressive privacy protections in recent years--could foreshadow how a potentially huge market for facial recognition technology is regulated by other states. The bill calls for companies and agencies that use facial recognition tools in areas accessible to the public to "provide a conspicuous and contextually appropriate notice" that faces may get scanned.
The identification of light sources is very important for the development of photonic technologies such as light detection and ranging (LiDAR), and microscopy. Typically, a large number of measurements are needed to classify light sources such as sunlight, laser radiation, and molecule fluorescence. The identification has required collection of photon statistics or quantum state tomography. In recently published work, researchers have used a neural network to dramatically reduce the number of measurements required to discriminate thermal light from coherent light at the single-photon level. In their paper, authors from Louisiana State University, Universidad Nacional Autónoma de México and Max-Born-Institut describe their experimental and theoretical techniques.
Today Flying Cloud Technology announces it has entered into an OEM relationship with Wireless Guardian. Wireless Guardian is the world's first forward-facing human threat detection system and the most effective investigative security solution for today's high-tech environment. Providing protection to patrons and facilities, Wireless Guardian tracks both security and pandemic threats up to a mile outside the facility's perimeter. "Flying Cloud is extremely happy to enter into this strategic partnership with Wireless Guardian. We feel that this partnership will showcase the incredible strengths of both companies. Wireless Guardian will be an invaluable data source that is fed into and analyzed by Flying Cloud. This data will allow our joint customers to not only detect someone entering their facility with a temperature, but with our patented AI models, we can clearly show where they went in a facility and show who they were in contact with. Flying cloud is now the only company that can track both the user and the data that they interact with," said Brian Christian, CEO of Flying Cloud Technology.