School of Mechatronic Engineering and Automation, Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, Shanghai University, Shanghai, China<&wdkj&>College of Horticulture, Hunan Agricultural University, Changsha, China<&wdkj&>Key Laboratory of Quality and Safety Regulating of Horticultural Crop Products, Ministry of Agriculture, Shanghai, China<&wdkj&>College of Horticulture, Hunan Agricultural University, Changsha, China
National Natural Science Foundation of China, Grant/Award Number: 52175102; Shanghai Science and Technology Innovation Program
机构署名：
本校为第一机构
院系归属：
园艺园林学院
摘要：
The development of agricultural robots and the promotion of agricultural production automation are important means to alleviate the shortage of agricultural labor. Fruit and vegetable detection is a prerequisite for accurate harvesting by robots. It directly determines the efficiency and quality of harvesting operations. In order to meet the requirements of target positioning and recognition of tomato harvesting robots, this paper studies tomato recognition technology based on YOLOv3 convolutional neural network algorithm. And the tomato detection process of the YOLOv3 model is presented. The ...
