Research on lemon quality grading detection based on improved YOLOv5s

Qirui Zhu; Shuiqiang Zhang

doi:10.1117/12.3031027

19 July 2024 Research on lemon quality grading detection based on improved YOLOv5s

Qirui Zhu, Shuiqiang Zhang

Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 131812J (2024) https://doi.org/10.1117/12.3031027
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

To address the lack of effective grading and processing methods in the current large-scale development of lemon cultivation in China, this study introduces a Class-guide feature extraction module on top of the existing YOLOv5s model. This further enhances the network's feature extraction capabilities and integrates the correlation between lemon detection and grading tasks. The study designs a multi-task learning algorithm that combines image-level and box-level fusion and incorporates defect detection and quality grading into a single task model through joint training. Experimental results show that the improved model achieves a 5% increase in mAP and mAP50-95 values compared to the original YOLOv5s model in detection, and an accuracy improvement of over 2.2% in classification compared to commonly used algorithms. The lemon quality grading detection method based on improved YOLOv5s achieves improved performance in both detection and grading tasks, meeting the practical application needs of the market.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qirui Zhu and Shuiqiang Zhang "Research on lemon quality grading detection based on improved YOLOv5s", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 131812J (19 July 2024); https://doi.org/10.1117/12.3031027

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KEYWORDS

Object detection

Feature extraction

Data modeling

Detection and tracking algorithms

Defect detection

Image fusion

Education and training

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