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Real-Time Object Recognition with Neuro-Fuzzy Controlled Workload-Aware Task Pipelining
November/December 2009 (vol. 29 no. 6)
pp. 28-43
Joo-Young Kim, Korea Advanced Institute of Science and Technology
Minsu Kim, Korea Advanced Institute of Science and Technology
Seungjin Lee, Korea Advanced Institute of Science and Technology
Jinwook Oh, Korea Advanced Institute of Science and Technology
Sejong Oh, Korea Advanced Institute of Science and Technology
Hoi-Jun Yoo, Korea Advanced Institute of Science and Technology

A proposed object recognition processor lightens its workload by estimating global region-of-interest features. A neuro-fuzzy controller performs intelligent ROI estimation by mimicking the human visual system, then manages the processor's overall pipeline stages using workload-aware task scheduling and applied database size control. The NFC performs workload-aware dynamic power management to reduce the proposed processor's power consumption.

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Index Terms:
multicore processor, object recognition, visual perception, three-stage task pipelined architecture, neuro-fuzzy controller, workload-aware dynamic power management
Citation:
Joo-Young Kim, Minsu Kim, Seungjin Lee, Jinwook Oh, Sejong Oh, Hoi-Jun Yoo, "Real-Time Object Recognition with Neuro-Fuzzy Controlled Workload-Aware Task Pipelining," IEEE Micro, vol. 29, no. 6, pp. 28-43, Nov.-Dec. 2009, doi:10.1109/MM.2009.102
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