High-performance real-time classification processor using conventional and neural processing techniques

Robert Shears

doi:10.1117/12.181038

29 July 1994 High-performance real-time classification processor using conventional and neural processing techniques

Robert Shears

Author Affiliations +

Proceedings Volume 2234, Automatic Object Recognition IV; (1994) https://doi.org/10.1117/12.181038
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

Future systems must intelligently preprocess an increasingly large volume of sensor data in real time within the constraints of an airborne environment. A compact, flightworthy, real time sensor processor has been developed which can host both conventional and neural processing algorithms. This will support a wide range of applications including high performance target classification from high resolution infrared imagery. The architecture features software reconfigurability to support different processing tasks and modular upgrade potential. Accurate classification of ship imagery has been demonstrated, using real airborne trials data produced under a range of operating conditions. The system is currently continuing to undergo airborne trials.

Citation Download Citation

Robert Shears, Robert Shears, } "High-performance real-time classification processor using conventional and neural processing techniques", Proc. SPIE 2234, Automatic Object Recognition IV, (29 July 1994); doi: 10.1117/12.181038; https://doi.org/10.1117/12.181038

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