AFNE-Net: Semantic Segmentation of Remote Sensing Images via Attention-Based Feature Fusion and Neighborhood Feature Enhancement
Understanding remote sensing imagery is vital for object observation and planning. However, the acquisition of optical images is inevitably affected by shadows and occlusions, resulting in local discrepancies in object representation. To address these challenges, this paper proposes AFNE-Net, a gene...
Saved in:
| Main Authors: | Ke Li, Hao Ji, Zhijiang Li, Zeyu Cui, Chengkai Liu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/14/2443 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Semantic enhancement and change consistency network for semantic change detection in remote sensing images
by: Zhenghao Jiang, et al.
Published: (2025-08-01) -
GLFFNet: Global–Local Feature Fusion Network for High-Resolution Remote Sensing Image Semantic Segmentation
by: Saifeng Zhu, et al.
Published: (2025-03-01) -
UAV-FAENet: Frequency-Aware and Attention-Enhanced Network for Remote Sensing Semantic Segmentation of UAV Imagery
by: Dongbo Zhou, et al.
Published: (2025-01-01) -
Multi-scale fusion semantic enhancement network for medical image segmentation
by: Zilong Zhang, et al.
Published: (2025-07-01) -
MFSM-Net: Multimodal Feature Fusion for the Semantic Segmentation of Urban-Scale Textured 3D Meshes
by: Xinjie Hao, et al.
Published: (2025-04-01)