D<sup>2</sup>SFormer: Dual Attention-Dynamic Bidirectional Transformer for Semantic Segmentation of Urban Remote Sensing Images
Semantic segmentation of urban remote sensing images (URSIs) is crucial for the development of smart cities and the acceleration of urban information. In view of the characteristics of URSIs with intricate backgrounds, dense distributions of feature objects, and varying object scales, we propose a d...
Saved in:
| Main Authors: | Yi Yan, Jiafeng Li, Jing Zhang, Liuqian Wang, Li Zhuo |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10981636/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Multimodal Prompt-Guided Bidirectional Fusion for Referring Remote Sensing Image Segmentation
by: Yingjie Li, et al.
Published: (2025-05-01) -
CAU<sup>2</sup>DNet: A Dual-Branch Deep Learning Network and a Dataset for Slum Recognition with Multi-Source Remote Sensing Data
by: Xi Lyu, et al.
Published: (2025-07-01) -
Dual Attention Dual-Resolution Networks for Real-Time Semantic Segmentation of Street Scenes
by: Baofeng Ye, et al.
Published: (2025-01-01) -
Dual Attention Equivariant Network for Weakly Supervised Semantic Segmentation
by: Guanglun Huang, et al.
Published: (2025-06-01) -
AFENet: An Attention-Focused Feature Enhancement Network for the Efficient Semantic Segmentation of Remote Sensing Images
by: Jiarui Li, et al.
Published: (2024-11-01)