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21 September 1998 Implementation of the morphological shared-weight neural network (MSNN) for target recognition on the Parallel Algebraic Logic (PAL) computer
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Abstract
The morphological shared-weight neural network (MSNN) is an effective approach to automatic target recognition. Implementation of the network in parallel is critical for real-time target recognition systems. Although there is significant parallelism inherent in the MSNN, it is a challenge to implement it on an SIMD parallel computer consisting of a large array of simple processing elements. This paper discusses issues related to detection accuracy and throughput in implementing the MSNN on the Parallel Algebraic Logic computer.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hongzheng Li, Hongchi Shi, Paul D. Gader, and James M. Keller "Implementation of the morphological shared-weight neural network (MSNN) for target recognition on the Parallel Algebraic Logic (PAL) computer", Proc. SPIE 3452, Parallel and Distributed Methods for Image Processing II, (21 September 1998); https://doi.org/10.1117/12.323468
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