Using YOLOv3 Algorithm with Pre- and Post-Processing for Apple Detection in Fruit-Harvesting Robot
Anna Kuznetsova, Tatiana Maleva, Vladimir Soloviev
- 发表年份
- 2020
- 引用次数
- 190
- 访问权限
- 开放获取
摘要
A machine vision system for detecting apples in orchards was developed. The system was designed to be used in harvesting robots and is based on a YOLOv3 algorithm with special pre- and post-processing. The proposed pre- and post-processing techniques made it possible to adapt the YOLOv3 algorithm to be used in an apple-harvesting robot machine vision system, providing an average apple detection time of 19 ms with a share of objects being mistaken for apples at 7.8% and a share of unrecognized apples at 9.2%. Both the average detection time and error rates are less than in all known similar systems. The system can operate not only in apple-harvesting robots but also in orange-harvesting robots.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991