Improved U-Net based on ResNet and SE-Net with dual attention mechanism for glottis semantic segmentation.

In previous tasks of glottis image segmentation, the position attention mechanism was rarely incorporated, neglecting the detailed information in glottis position detection. Aiming to improve the U-Net architecture, this study introduces the dual attention mechanism based on the squeeze and excitation (SE)-Net model. This mechanism can integrate traditional channel attention with position attention mechanisms to effectively adjust the weights of crucial features and significance of positions.