English

Deep Attention Unet: A Network Model with Global Feature Perception Ability

Computer Vision and Pattern Recognition 2024-01-18 v2 Image and Video Processing

Abstract

Remote sensing image segmentation is a specific task of remote sensing image interpretation. A good remote sensing image segmentation algorithm can provide guidance for environmental protection, agricultural production, and urban construction. This paper proposes a new type of UNet image segmentation algorithm based on channel self attention mechanism and residual connection called . In my experiment, the new network model improved mIOU by 2.48% compared to traditional UNet on the FoodNet dataset. The image segmentation algorithm proposed in this article enhances the internal connections between different items in the image, thus achieving better segmentation results for remote sensing images with occlusion.

Keywords

Cite

@article{arxiv.2304.10829,
  title  = {Deep Attention Unet: A Network Model with Global Feature Perception Ability},
  author = {Jiacheng Li},
  journal= {arXiv preprint arXiv:2304.10829},
  year   = {2024}
}

Comments

The experiment was inadequate and the experimental method needed major changes

R2 v1 2026-06-28T10:13:28.128Z