关键词: 太阳能电池, 缺陷分割, 多尺度特征, 门控融合, 上下文注意力

Abstract: This paper proposes an improved semantic segmentation network based on cross-gated fusion due to poor segmentation accuracy caused by small and weak defects such as broken grids,scratches and black spots on the surface of solar cells.Firstly,to address the problem of small defects in solar cells,a cross-gated fusion module is proposed,which selectively fuses multi-scale information in the network through the gating mechanism.The module makes full use of low-level detailed information and high-level semantic information,enhances the feature representation of small defects,and improves the ability to obtain full-text information by combining the context module.Secondly,to further solve the problem of weak edge information of solar cell defects,the PointRend module is introduced to sample the points on the defect edge,and an adaptive subdivision strategy is implemented for the uncertain points on the edge to realize fine segmentation of the defect edge.Finally,the experimental results show that the mIoU of the proposed method on the data set of solar EL component batteries reaches 65.53%.Compared with the existing semantic segmentation algorithm,the proposed method can effectively refine the target boundary and handle small and weak defects better.