"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.
Technology companies of all sizes and in locations all around the world are developing AI-driven products aimed at reducing operating costs, improving decision-making and enhancing consumer services across a range of client industries. The sum of these drivers -- new programming techniques, more data and faster chips -- has seen AI converge with human-level performance in the key areas of image classification and speech recognition over recent years (see EXHIBIT 2). Chipmakers stand to benefit from increased demand for processing power, particularly makers of graphical processing units for AI program training. And internet companies with AI at the core of their consumer services (such as digital assistants and new software features) stand to benefit directly from improvements in speech recognition and image classification.
W-net is a self-supervised convolutional neural network architecture to learn to predict depth maps from pairs of stereo images. The network is trained directly on pairs of stereo images to jointly reconstruct the left view from the right view and the rihgt view from the left view, using learned disparity maps and the L1 norm as a reconstruction error metric. A probabilistic selection layer that applies simple geometric transformations is used to reconstruct the left/right view from the right/left view and the corresponding disparity map. The third particulrity of w-net is the presence of both a probabilistic selection layer, which uses the calculated disparity to apply geometrical transformations from the left to right images, as well as a gradient layer which computes the spatial gradient of the calculated disparity map in order to enforce some level of smoothness with the help of an auxiliary loss function.
Unibap's Intelligent Vision System platform provides increased productivity in smart factories and advanced robotics by combining hardware reliability of aerospace heritage, machine vision, and artificial intelligence (AI). Typical applications for IVS are intelligent industrial automation, intelligent 3D vision, machine tool inspection, agricultural robotics, service robotics, and autonomous surveillance. IVS supports Unibap's Deep Delphi software environment which includes Deep Learning and real-time control capabilities built on the software and computing infrastructure from Unibap's spaceflight proven SpaceCloud line of products. IVS products are interoperable with cloud based services, including Unibap's cloud services for Deep Learning training, remote health monitoring and performance analysis, and Fog based industrial networks while offering local execution of machine learning algorithms.
Roughly 10 million people tune in every day to watch the more than 2 million people who stream their games on platforms like the Amazon-owned Twitch. To keep viewers hooked, gamers dip into an evolving bag of tricks, for example, sharing performance statistics, playing music and displaying live chat comments in a frame that surrounds the view of the game itself. The team observed them as they viewed a single gamer, first during a 1-hour session without the biometric data in the video stream, and then 1 hour with. In a survey, 70 per cent said they felt more connected when they could view the player's physiological state.
They took a high-energy CT scan of a 74-million-year-old skull that came from a dinosaur dubbed the Bisti Beast, which was found in northwestern New Mexico about 20 years ago and is related to the Tyrannosaurus rex, the Los Alamos National Laboratory reported, calling the work the highest resolution scan scientists have ever taken of a tyrannosaur. Researchers have scanned the skull of Bistahieversor sealeyi, a type of tyrannosaur found in New Mexico. According to Los Alamos National Lab, the scientists are expected to present more detailed results for the Bisti Beast at the annual Society of Vertebrate Paleontology meeting this month in Canada. Researchers have scanned the skull of Bistahieversor sealeyi, a type of tyrannosaur found in New Mexico.
The additions are an iris-authentication front-facing option, an "Entry-Level Computer Vision" setup and a "Premium Computer Vision" kit. Of the three new modules, the most intriguing is the premium computer vision kit. That option is capable of active depth sensing, using an infrared illuminator, IR camera and a 16-megapixel (or 20-MP, depending on configuration) RGB camera. And according to Qualcomm, its iris authentication module can read your eyes even when you have sunglasses on -- something the company's representatives demonstrated effectively at the briefing.
Chen says the technique could eventually create game worlds that truly resemble the real world. The AI was trained on 3000 images of German streets, so when it comes across part of the photo labelled "car" it draws on its existing knowledge to generate a car there in its own creation. That's easier said than done, however, as each component in the training images needs to be labelled by hand, and creating a data set with that level of detail is extremely labour-intensive. But when it comes to building worlds in virtual reality, that dreamlike nature might not be such a bad thing, says Snavely.
Sensors were installed in top-down views above hand-sanitizer gel dispensers, in side-views overlooking the corridors, inside patient rooms, and in the corners of rooms overlooking sinks and patient beds. Sensors were installed in top-down views above hand-sanitizer gel dispensers, in side-views overlooking the corridors, inside patient rooms, and in the corners of rooms overlooking sinks and patient beds. By contrast, a single undercover person tracking hand washing behavior was only 63 per cent accurate in detecting if a person complied with hand washing standards. By contrast, a single undercover person tracking hand washing behavior was only 63 per cent accurate in detecting if a person complied with hand washing standards.
Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. Core to many of these applications are visual recognition tasks such as image classification, localization and detection. Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. Core to many of these applications are visual recognition tasks such as image classific... more
Along those lines, Alizadeh and his team at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed "Pensieve," an artificial intelligence (AI) system that uses machine learning to pick different algorithms depending on network conditions. "Our system is flexible for whatever you want to optimize it for," says PhD student Hongzi Mao, who was lead author on a related paper with Alizadeh and PhD student Ravi Netravali. Researchers have also tried to combine the two methods: A system out of Carnegie Mellon University outperforms both schemes using "model predictive control" (MPC), an approach that aims to optimize decisions by predicting how conditions will evolve over time. Content providers like YouTube could customize Pensieve's reward system based on which metrics they want to prioritize for users.