CMOL crossnets as pattern classifiers

Authors:
Jung Hoon Lee;Konstantin K. Likharev
Affiliations:
Stony Brook University, Stony Brook, NY;Stony Brook University, Stony Brook, NY
Venue:
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
Year:
2005

Citing 2
Cited 6

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Abstract

This presentation has two goals: (i) to review the recently suggested concept of bio-inspired CrossNet architectures for future hybrid CMOL VLSI circuits and (ii) to present new results concerning the prospects and problems of using these neuromorphic networks as classifiers of very large patterns, in particular of high-resolution optical images. We show that the unparalleled density and speed of CMOL circuits may enable to perform such important and challenging tasks as, for example, online recognition of a face in a high-resolution image of a large crowd.