Agc Flat Glass North America, Inc.

Norlitech, LLC

Other

Silicon Recognition, Inc.

Guy Paillet

Anne Menendez

Donald Francis Specht

Toshikazu Hori

Jeffrey M Woo

The present invention is directed to an apparatus which can acquire, readout and perceive a scene based on the insertion, or embedding of photosensitive elements into or on a transparent or semi-transparent substrate such as glass or plastic. The substrate itself may act as the optical device which deflects the photons of an incident image into the photosensitive elements. A digital neural memory can be trained to recognize patterns in the incident photons. The photosensitive elements and digital neural memory elements may be arranged with light elements controlled in accordance with the patterns detected. In one application, intelligent lighting units provide light while monitoring surroundings and/or adjusting light according to such surroundings. In another application, intelligent displays display images and/or video while monitoring surroundings and/or adjusting the displayed images and/or video in accordance with such surroundings.

Monolithic image perception device and method

An apparatus which can acquire, readout and perceive a scene based on the insertion, or etching of photosensitive elements into or on a transparent or semi-transparent substrate such as glass. The substrate itself acts as the optical device which deflects the photons incident to the reflected image into the photosensitive elements. Photosensitive elements are interconnected together by a transparent or opaque wiring. A digital neural memory can be trained to recognize specific scenery such as a human face, an incoming object, a surface defect, rain drops on a windshield and more. Other applications include image-perceptive car headlight and flat panel display detecting and identifying the viewer's behavior (gaze tracking, face recognition, facial expression recognition and more). Yet another application includes sliding doors perceiving the direction and speed of an individual coming towards that door. Yet another application includes permanent damage detection (texture change) in dam, bridge or other manmade construction.

A neural network integrated circuit comprises many neuron circuits each with a distance resister that is compared in a competition for the closest-hit with all the other neurons. Such closest-hit comparison is conducted bit-by-bit over the many bit positions of a distance measure in binary format each time after the neurons fire. A single-wire AND-bus interconnects every neuron in a whole system. Each neuron drives the single-wire AND-bus with an open-collector buffer. All neurons press the single-wire AND-bus with their respective distance measures in successive cycles, starting with the most significant bit. For example, a fourteen-bit binary distance word requires fourteen comparison cycles. Any neuron that sees a &ldquo;0&rdquo; on the single-wire AND-bus when its own corresponding bit in its distance measure is a &ldquo;1&rdquo;, automatically drops from the competition. By the time the least significant bit cycle is run, a single closest distance will have been determined. Such neuron that wins announces itself with an identifying code.

Neural network integrated circuit with fewer pins

A recognition system comprises at least two field-programmable logic array devices connected to a common vector-input port of an array of a zero-instruction-set computers. Each field-programmable logic array device is configured to preprocess data from different respective media inputs and provide feature extraction vectors to the common vector-input port. Neural networks within the zero-instruction-set computer recognize the input patterns by comparing in parallel their vectors with those stored in each neural network cell. A variety of recognition jobs are made possible by changing the programming on-the-fly of the field-programmable logic array devices to suit each new job.

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Corte Madera, CA, United States of America

Guy Paillet