A 12-nm 0.62-1.61 mW Ultra-Low Power Digital CIM-based Deep-Learning System for End-to-End Always-on Vision - researchr publication authors

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En-Jui Chang, Cheng-Xin Xue, Chetan Deshpande, Gajanan Jedhe, Jenwei Liang, Chih-Chung Cheng, Hung-Wei Lin, Chia-Da Lee, Sushil Kumar, Kim Soon Jway, Zijie Guo, Ritesh Garg, Allen-CL Lu, Chien-Hung Lin, Meng-Han Hsieh, Tsung-Yao Lin, Chih-Cheng Chen. A 12-nm 0.62-1.61 mW Ultra-Low Power Digital CIM-based Deep-Learning System for End-to-End Always-on Vision. In 2023 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits), Kyoto, Japan, June 11-16, 2023. pages 1-2, IEEE, 2023. [doi]

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