Defect recognition is crucial in steel production and quality control, but performing this detection task accurately presents significant challenges. ConvNeXt, a model based on self-attention mechanism, has shown excellent performance in image classification tasks. To further enhance ConvNeXt’s ability to classify defects on steel surfaces, we propose a network architecture called ESG-ConvNeXt. First, in the image processing stage, we introduce a serial multi-attention mechanism approach.
This met
Source: NDT