This study proposed a novel detection method for crayfish weight classification based on an improved Swin-Transformer model. The model demonstrated a Mean Intersection over Union (MIOU) of 90.36% on the crayfish dataset, outperforming the IC-Net, DeepLabV3, and U-Net models by 17.44%, 5.55%, and 1.01%, respectively. Furthermore, the segmentation accuracy of the Swin-Transformer model reached 99.0%, surpassing the aforementioned models by 1.25%, 1.73%, and 0.46%, respectively. To facilitate weight prediction of crayfish from segmented images, this study also investigated the correlation between...
