A5033434254- Remote Sensing and LiDAR Applications
- Remote Sensing in Agriculture
- Automated Road and Building Extraction
- Hydrology and Sediment Transport Processes
- Urban Green Space and Health
Chinese Academy of Sciences
2024-2025
University of Chinese Academy of Sciences
2024-2025
Aerospace Information Research Institute
2024-2025
Riverbank sand overexploitation is threatening the ecology and shipping safety of rivers. The rapid identification riverbank mining areas from satellite images extremely important for ecological protection management. Image segmentation methods based on AI technology are gradually becoming popular in academia industry. However, traditional neural networks have complex structures numerous parameters, making them unsuitable meeting needs extraction large areas. To improve efficiency, we...
Street trees are of great importance to urban green spaces. Quick and accurate segmentation street from high-resolution remote sensing images is significance in space management. However, traditional methods can easily miss some targets because the different sizes trees. To solve this problem, we propose Double-Branch Multi-Scale Contextual Network (DB-MSC Net), which has two branches a (MSC) block encoder. The MSC combines parallel dilated convolutional layers transformer blocks enhance...