A machine-learning based intelligent vision SoC implemented on a 9.3 mm 2 die in a 40nm CMOS process is presented. The architecture realizes 140 meters active distance at 60fps and 60 meters at 300fps under Quad-VGA (1280×960) resolution while maintaining above 90% detection rate for versatile automotive applications. The system supports 64 object tracking and prediction. It raises 1.62× improvement on power efficiency and at least 1.79× increase on frame rate with the proposed knowledge-based tracking processor. The chip achieves 354.2fps/W and 3.01TOPS/W power efficiency with 69mW average power consumption.
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Tsai et al. (2012) studied this question.
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