Research on Wood Surface Defect Recognition Algorithm Based on Deep Learning
China is a large country in the production,manufacturing and export of wood and wood products,and the surface defects of wood panels will reduce the external quality and internal strength of wood panels,which will affect the processing and production process of wood.Based on the self-made wood surface defect data set,this paper con-ducts comprehensive testing and comparative analysis of several mainstream loss functions on the YOLOv5s model.This paper aims to expand the application of deep learning model in the field of wood defect detection,in order to provide a new idea for automatic inspection of wood surface defects.
NETL
NSTL
万方数据
