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A 201.4 GOPS 496 mW Real-Time Multi-Object Recognition Processor With Bio-Inspired Neural Perception Engine
2010
IEEE Journal of Solid-State Circuits
A 201.4 GOPS real-time multi-object recognition processor is presented with a three-stage pipelined architecture. Visual perception based multi-object recognition algorithm is applied to give multiple attentions to multiple objects in the input image. For human-like multi-object perception, a neural perception engine is proposed with biologically inspired neural networks and fuzzy logic circuits. In the proposed hardware architecture, three recognition tasks (visual perception, descriptor
doi:10.1109/jssc.2009.2031768
fatcat:343tnykb7zd5dgpuz5pjdxuboi