Fruit image recognition based on YOLOv5

Lijuan Qin; Yubin Zhu

doi:10.1117/12.2675231

25 May 2023 Fruit image recognition based on YOLOv5

Lijuan Qin, Yubin Zhu

Proceedings Volume 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022); 126361L (2023) https://doi.org/10.1117/12.2675231
Event: Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 2022, Shenyang, China

Abstract

The fruit picking robot based on YOLOv5 has great development and application prospect in many fields in today's society, among which the target recognition accuracy of fruit image is the key. In view of the low recognition accuracy of small target fruit, this paper improves the data enhancement in the data pre-processing stage based on the YOLOv5 algorithm. The improved image recognition rate is 0.064s and mAP@0.5 is 0.91530. The optimized algorithm has high accuracy and certain practicability, which lays a foundation for automatic picking and other services in the future.

Citation Download Citation

Lijuan Qin and Yubin Zhu "Fruit image recognition based on YOLOv5", Proc. SPIE 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 126361L (25 May 2023); https://doi.org/10.1117/12.2675231

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