| abstract |
A eucalyptus veneer defect image detection system and detection method, which realizes the identification of eucalyptus veneer defects, wherein the identification of the defect category is balanced by the Bbox-cover method, and the designed aggregation module AGM is used to perform channel information on YOLOv5. Effective fusion with pixel information can improve the detection accuracy of eucalyptus wood defects. Finally, a calculation method of defect area is designed to meet the needs of users to screen and count different defect sizes. |