CV-YOLOv10-AR-M: Foreign Object Detection in Pu-Erh Tea Based on Five-Fold Cross-Validation

CV-YOLOv10-AR-M: Foreign Object Detection in Pu-Erh Tea Based on Five-Fold Cross-Validation

To address the problem of detecting foreign bodies in Pu-erh tea, this study proposes an intelligent detection method based on an improved YOLOv10 network. By introducing the MPDIoU loss function, the YOLOv10 network is optimized to effectively enhance the positioning accuracy of the model in comple...

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Bibliographic Details
Main Authors: Wenxia Yuan, Chunhua Yang, Xinghua Wang, Qiaomei Wang, Lijiao Chen, Man Zou, Zongpei Fan, Miao Zhou, Baijuan Wang
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Foods
Subjects:
CV-YOLOv10-AR-M network
MPDIoU
AssemFormer
Rectangular Self-Calibrated Module
Online Access:https://www.mdpi.com/2304-8158/14/10/1680
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