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1 February 1994 Hybrid architecture for KIMS object recognition in a multicontext scene
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Proceedings Volume 2093, Substance Identification Analytics; (1994) https://doi.org/10.1117/12.172537
Event: Substance Identification Technologies, 1993, Innsbruck, Austria
Abstract
In a multicontext scene where several objects may be occluded or scenes may change rapidly, a single paradigm for computer vision may not be sufficient. The demand to adjust and learn new environment is therefore a challenging modeling problem in computer vision research. In response to this challenge we have developed a hybrid architecture which combines classical pattern recognition algorithms with fuzzy knowledge-base and Hopfield Neural Network. We also present elementary results obtained from this effort.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Celestine A. Ntuen, Evi H. Park, Jung H. Kim, and Shiu M. Cheung "Hybrid architecture for KIMS object recognition in a multicontext scene", Proc. SPIE 2093, Substance Identification Analytics, (1 February 1994); https://doi.org/10.1117/12.172537
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