YOLOv11-GATFormer: A unified framework for wood surface defect detection and classification
Published online on May 05, 2026
Abstract
Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, Ahead of Print.
This study aims to develop a robust and accurate framework for classifying wood surface defects in industrial settings, where traditional methods struggle with variability and overlapping textures. The proposed approach combines YOLOv11 for precise defect ...
This study aims to develop a robust and accurate framework for classifying wood surface defects in industrial settings, where traditional methods struggle with variability and overlapping textures. The proposed approach combines YOLOv11 for precise defect ...