A neural network incorporating direct optical imaging

A compact neural network architecture (10) is trainable to sense and classify an optical image (Figs 3, 6) directly projected onto it. The system is based upon the combination of a two-dimensional array (12) of amorphous silicon photoconductors (18) and a liquid-crystal spatial light modulator (20;...

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Bibliographic Details
Main Author STEARNS, RICHARD G
Format Patent
LanguageEnglish
French
German
Published 28.05.1997
Edition6
Subjects
ANALOGUE COMPUTERS
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
OPTICAL COMPUTING DEVICES
PHYSICS
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Summary:A compact neural network architecture (10) is trainable to sense and classify an optical image (Figs 3, 6) directly projected onto it. The system is based upon the combination of a two-dimensional array (12) of amorphous silicon photoconductors (18) and a liquid-crystal spatial light modulator (20; Fig. 2). Appropriate filtering of the incident optical image upon capture is incorporated into the network training rules, through a modification of the standard backpropagation training algorithm. Training of the network (10) on two image classification problems is described: the recognition of handprinted digits (Fig. 3), and facial recognition (Fig. 6). The network (10), once trained is capable of standalone operation, sensing an incident image and outputting a final classification signal in real time.
Bibliography:Application Number: EP19950309053