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- W2974161802 abstract "In the past few years, the demand for intelligence of IoT front-end devices has dramatically increased. However, such devices face challenges of limited on-chip resources and strict power or energy constraints. Recent progress in binarized neural networks has provided promising solutions for front-end processing system to conduct simple detection and classification tasks by making trade-offs between the processing quality and the computation complexity. In this paper, we propose a mixed-signal perception chip, in which an ADC-free 32×32 image sensor and a BNN processing array are directly integrated with a 180nm standard CMOS process. Taking advantage of the ADC-free processing architecture, the whole processing system only consumes 1.8mW power, while providing up to 545.4 GOPS/W energy efficiency. The implementation performance and energy efficiency are comparable with the state-of-the-art designs in much more advanced CMOS technologies. This work provides a promising alternative for low-power IoT intelligent applications." @default.
- W2974161802 created "2019-09-26" @default.
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- W2974161802 date "2019-07-01" @default.
- W2974161802 modified "2023-09-27" @default.
- W2974161802 title "A 1.8mW Perception Chip with Near-Sensor Processing Scheme for Low-Power AIoT Applications" @default.
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- W2974161802 doi "https://doi.org/10.1109/isvlsi.2019.00087" @default.
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