CASI-Net: A Novel and Effect Steel Surface Defect Classification Method Based on Coordinate Attention and Self-Interaction Mechanism

CASI-Net: A Novel and Effect Steel Surface Defect Classification Method Based on Coordinate Attention and Self-Interaction Mechanism

Blog Article

The surface defects of a hot-rolled strip will adversely affect the appearance and quality of industrial products.Therefore, the timely identification of hot-rolled strip surface defects is of great significance.In order to improve the efficiency and accuracy of surface defect detection, a lightweight network based on coordinate attention and self-interaction (CASI-Net), which integrates channel domain, spatial information, and a self-interaction module, ngetikin is proposed to automatically identify six kinds of hot-rolled steel strip surface defects.

In this paper, we use coordinate attention to embed location information into channel attention, which enables the CASI-Net to locate the region of defects more accurately, thus contributing to better recognition and classification.In addition, features are converted into aggregation features from the horizontal and vertical direction attention.Furthermore, a self-interaction module is proposed to interactively fuse the extracted feature information to here improve the classification accuracy.

The experimental results show that CASI-Net can achieve accurate defect classification with reduced parameters and computation.