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A comprehensive analysis of DAC-SDC FPGA low power object detection challenge
《Science China(Information Sciences)》2024年第8期296-316,共21页Jingwei ZHANG Guoqing LI Meng ZHANG Xinye CAO Yu ZHANG Xiang LI Ziyang CHEN Jun YANG 
supported by Key R&D Program of Guangdong Province(Grant No.2021B1101270006);Shandong Provincial Natural Science Foundation(Grant No.ZR2023QF056);Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.SJCX22-0051).
The lower power object detection challenge(LPODC)at the IEEE/ACM Design Automation Conference is a premier contest in low-power object detection and algorithm(software)-hardware co-design for edge artificial intellige...
关键词:tiny machine learning object detection convolutional neural networks algorithm-hardware co-design low power field programmable gate array 
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