Optoelectronic neural processor for smart vision applications

Abstract

The implementation of a vision system in which the processing core is based on an optoelectronic neural network design is described. The vision system captures an image using a complimentary metal-oxide semiconductor (CMOS) image sensor, and the optoelectronic neural processor performs the classification among a set of sample patterns. The neural-network hardware architecture is based on an optical broadcast of inputs to an electronic array of processing elements, one per class. The benefit of this optoelectronic architecture, and thus the vision application, is that it is potentially scalable to a very large number of processing elements operating in parallel and at very high speed.

Keywords:

• OPTOELECTRONIC NEURAL NETWORK
• IMAGE CLASSIFICATION
• HOPFIELD NETWORK