Processing Near Sensor Architecture in Mixed-Signal Domain With CMOS Image Sensor of Convolutional-Kernel-Readout Method

In the era of Artificial Intelligence (AI), bio-inspired perceptual computing system design brings favorable opportunities, while still facing considerable challenges in the meantime. Especially for tasks of image recognition in power-limited vision-based Internet of Things (IoT) devices, energy con...

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Veröffentlicht in:	IEEE transactions on circuits and systems. I, Regular papers Jg. 67; H. 2; S. 389 - 400
Hauptverfasser:	Chen, Zhe, Zhu, Huifeng, Ren, Erxiang, Liu, Zheyu, Jia, Kaige, Luo, Li, Zhang, Xuan, Wei, Qi, Qiao, Fei, Liu, Xinjun, Yang, Huazhong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.02.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Analog to digital conversion Analog to digital converters Architecture Artificial intelligence binarized-weight neural network Biomimetics Circuits CMOS CMOS image sensors Computer architecture Convolution Domains Energy conversion efficiency Energy efficiency Energy management Fault tolerance Internet of Things Kernel Kernels lower power IoT Neural networks Object recognition Power consumption Power efficiency Power management processing near sensor Sensor arrays Sensors Signal processing Smart CMOS image sensor Systems design Task analysis Vision Visual perception Visual signals
ISSN:	1549-8328, 1558-0806
Online-Zugang:	Volltext
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