Consumers now experience AI mostly through image recognition to help categorize digital photographs and speech recognition that helps power digital voice assistants such as Apple Inc's Siri or Amazon.com But at a press briefing in San Francisco two days before Ng's Landing.ai In many factories, workers look over parts coming off an assembly line for defects. Ng showed a video in which a worker instead put a circuit board beneath a digital camera connected to a computer and the computer identified a defect in the part. Ng said that while typical computer vision systems might require thousands of sample images to become "trained," Landing.ai's
Google's Hartmut Neven demonstrates his visual-search app by snapping a picture of a Salvador Dali clock in his office building. Google and other tech companies are racing to improve image-recognition software Computers can recognize some objects in images, but not all Google's engineering director predicts the technology will fully mature in 10 years Google's engineering director predicts the technology will fully mature in 10 years Santa Monica, California (CNN) -- Computers used to be blind, and now they can see. Thanks to increasingly sophisticated algorithms, computers today can recognize and identify the Eiffel Tower, the Mona Lisa or a can of Budweiser. Still, despite huge technological strides in the last decade or so, visual search has plenty more hurdles to clear. At this point, it would be quicker to describe the types of things an image-search engine can interpret instead of what it can't.
Paul F. Hemler, Thilaka Sumanaweera, Ramani Pichumani Petra A. van den Elsen, Sandy Napel, John Drace, John Adler Stanford University Medical Center, Stanford University, Stanford CA Abstract This paper describes a semiautomatic system for registering and visualizing CT (Computer Tomography) and MR (Magnetic Resonance) images the cervical spine. Registration requires identifying similar objects or structures in each image set. Identifying similar structures for this application is complicated because complementary imaging modalities are used. Following structure identification, the mapping transformation from one image set to the other can be determined using a nonlinear optimization procedure. The final step is visualizing the results of the registered images sets.
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Amazon.com Inc. acquired artificial-intelligence startup Orbeus Inc., according to a person familiar with the matter, part of a broader push by the world's largest Internet retailer into smart software for its cloud-computing and connected-device businesses. The acquisition took place in the fall of 2015, said the person who asked not to be identified because Amazon hasn't announced the deal. An Amazon spokeswoman and representatives at Sunnyvale, California-based Orbeus, including Chief Executive Officer Yi Li, did not respond to requests for comment. An online search shows that the startup's domain name, Orbe.us, is owned by registrant Amazon Hostmaster, part of an Amazon subsidiary called Amazon Technologies Inc. Orbeus developed photo-recognition technology based on a powerful type of AI called neural networks and made this available as a consumer application, as well as a service for other companies and developers called ReKognition. It automatically categorized and identified the contents of photos.