DSIA U-Net: deep shallow interaction with attention mechanism UNet for remote sensing satellite images

Semantic segmentation of high-resolution images from remote sensing is crucial across various sectors. However, due to limitations in computational resources and the complexity of network architectures, many sophisticated semantic segmentation models struggle with efficiency in real-world applications, leading to an interest in developing lightweight model like borders. These models often employ a dual-branch structure, which balances processing speed and performance effectively. Yet, this design typically falls short in leveraging shallow structural information to enrich the dual branches with comprehensive multiscale data. Additionally, the lightweight components struggle to capture the global contextual…

• PN
  Princess Nourah Bint Abdulrahman University

  Award: PNURSP2025R10
• MO
  Ministry of Education, India