Real time semantic segmentation network of wire harness terminals based on multiple receptive field attention

Abstract

Abstract： Recently， wire harnesses are widely used.The harness terminal， an important component of a harness， requires strict quality inspection.Therefore， to improve the accuracy and efficiency of harness terminal quality detection， a real-time semantic segmentation network using multiple receptive field (MRF) attention， called MRF-UNet， is proposed in this study.First， an MRF attention module is used as the basic module for network feature extraction， improving the feature extraction and generalization abil• ities of the model.Second， feature fusion is used to effect jump connections and reduce the computational load of the model.Finally， deconvolution and convolution are used for feature decoding to reduce the net• work depth and improve the algorithm's performance.The experimental results demonstrate that the mean intersection over union， mean pixel accuracy and dice coefficient of the MRF-UNet algorithm on the har• 文章编号 1004-924X