Design of Algorithm for Apple Rapid Positioning Based on YOLO Target Detection Model

被引：0
|
作者：
Zheng Jie [1 ]
Liu Jie [1 ]
Gong Kun [1 ]
Niu Zijie [1 ]
机构：
[1] Northwest Agr & Forestry Univ, Coll Mech & Elect Engn, Yangling, Shaanxi, Peoples R China
来源：
PROCEEDINGS OF 2021 2ND INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INFORMATION SYSTEMS (ICAIIS '21) | 2021年
关键词：
Apple positioning; YOLO; deep learning; object detection;
D O I：
10.1145/3469213.3470376
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The accurate recognition and location of apple can realize the precise picking of apples. Aiming at solving the problem of Apple rapid positioning, this paper uses the algorithm on YOLOv4 target detection model to extract the features of the dataset and train the deep-learning. Moreover, it combines the monocular camera and the user interface, and finally realizes a rapid positioning system of apple based on deep-learning. The final loss value of the trained model is only 3.872, which shows that the model performs well in positioning.
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页数：4
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