supported in part by the National Natural Science Foundation of China[grant numbers 52265041 and 31901417];the Open Subjects of Zhejiang Provincial Key Laboratory for Agricultural Intelligent Equipment and Robotics,China[grant number 202ZJZD2202];the Graduate School-level Research and Innovation Program of Xinjiang Agricultural University,China[grant number XJAUGRI2023021].
Harvesting robots had difficulty extracting filament phenotypes for small,numerous filaments,heavy cross-obscuration,and similar phenotypic characteristics with organs.Robots experience difficulty in localizing under ...
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...