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A 1.2mW On-line Learning Mixed-mode Intelligent Inference Engine for Low Power Real-time Object Recognition Processor

A 1.2mW On-line Learning Mixed-mode Intelligent Inference Engine for Low Power Real-time Object Recognition Processor
학술지명 IEEE Transactions On Very Large Scale Integration(VLSI) Systems ISSN 1063-8210
SCI 유무 SCI(E) 게재연월 2013-05 Vol. 21 No. 5
표준화된 순위정보영향력지수 71.43 IF 1.219 Citation 9

A 1.2mW On-line Learning Mixed-mode Intelligent Inference Engine for Low Power Real-time Object Recognition Processor
저자 JinWook Oh, SeungJin Lee, HoiJun Yoo
초록
Object recognition is computationally intensive and it is challenging to meet 30-f/s real-time processing demands under sub-watt low-power constraints of mobile platforms even for heterogeneous many-core architecture. In this paper, an intelligent inference engine (IIE) is proposed as a hardware controller for a many-core processor to satisfy the requirements of low-power real-time object recognition. The IIE exploits learning and inference capabilities of the neurofuzzy system by adopting the versatile adaptive neurofuzzy inference system (VANFIS) with the proposed hardware-oriented learning algorithm. Using the programmable VANFIS, the IIE can configure its hardware topology adaptively for different target classifications. Its architecture contains analog/digital mixed-mode neurofuzzy circuits for updating online parameters to increase attention efficiency of object recognition process. It is implemented in 0.13-μm CMOS process and achieves 1.2-mW power consumption with 94% average classification accuracy within 1-μs operation delay. The 0.765-mm2 IIE achieves 76% attention efficiency and reduces power and processing delay of the 50-mm2 image processor by up to 37% and 28%, respectively, when 96% recognition accuracy is achieved.
keyword Mixed-mode processor, neurofuzzy, object recognition, VLSI.

A 1.2mW On-line Learning Mixed-mode Intelligent Inference Engine for Low Power Real-time Object Recognition Processor
과제명 실시간 3D 이미징 및 디스플레이를 위한 초고속 병렬처리 프로세서 기술
연구기관 한국과학기술원 연구책임자 유회준