FML-Swin: An Improved Swin Transformer Segmentor for Remote Sensing Images
Semantic segmentation of urban remote sensing images is a very challenging task. Due to the complex background, occlusion overlap and small scale target of urban remote sensing image, the semantic segmentation results have some defects such as target confusion and similarity, target boundary ambigui...
Saved in:
| Main Authors: | Tianren Wu, Wenqin Deng, Rui Lin, Junzhe Jiang, Xueyun Chen |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10966862/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Aquaculture Areas Extraction Model Using Semantic Segmentation from Remote Sensing Images at the Maowei Sea of Beibu Gulf
by: Weirong Qin, et al.
Published: (2025-05-01) -
GLFFNet: Global–Local Feature Fusion Network for High-Resolution Remote Sensing Image Semantic Segmentation
by: Saifeng Zhu, et al.
Published: (2025-03-01) -
Low resolution remote sensing object detection with fine grained enhancement and swin transformer
by: Zhijing Xu, et al.
Published: (2025-07-01) -
Swin-FSNet: A Frequency-Aware and Spatially Enhanced Network for Unpaved Road Extraction from UAV Remote Sensing Imagery
by: Jiwu Guan, et al.
Published: (2025-07-01) -
MFPI-Net: A Multi-Scale Feature Perception and Interaction Network for Semantic Segmentation of Urban Remote Sensing Images
by: Xiaofei Song, et al.
Published: (2025-07-01)