Abstract

The article is dedicated to a method of “multi-attention mechanism” collocation to improve the detection ability of neural networks for textile defects. The “multi-attention mechanism” that combines channel attention and spatial attention in neural networks is presented to improve the feature extraction ability of defects. The results indicate that this method has a high detection rate for difficult-to-detect samples such as small defects, uneven density defects, and easily confused defects, among which the detection rate of stains, weft defects, and holes can reach more than 75%, and the detection rate of edge, erase and weave can reach more than 90%.

Keywords:Textile defects detection; Attention mechanism; Multi-attention; Mechanism collocation; Neural networks