AFENet: An Attention-Focused Feature Enhancement Network for the Efficient Semantic Segmentation of Remote Sensing Images
The semantic segmentation of high-resolution remote sensing images (HRRSIs) faces persistent challenges in handling complex architectural structures and shadow occlusions, limiting the effectiveness of existing deep learning approaches. To address these limitations, we propose an attention-focused f...
Saved in:
| Main Authors: | Jiarui Li, Shuli Cheng |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-11-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/16/23/4392 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Multi-Source Remote Sensing Images Semantic Segmentation Based on Differential Feature Attention Fusion
by: Di Zhang, et al.
Published: (2024-12-01) -
Multilevel Feature Interaction Network for Remote Sensing Images Semantic Segmentation
by: Hongkun Chen, et al.
Published: (2024-01-01) -
Construction of Multi-Scale Fusion Attention Unified Perceptual Parsing Networks for Semantic Segmentation of Mangrove Remote Sensing Images
by: Xin Wang, et al.
Published: (2025-01-01) -
Adjacent-Scale Multimodal Fusion Networks for Semantic Segmentation of Remote Sensing Data
by: Xianping Ma, et al.
Published: (2024-01-01) -
Semantic segmentation network for mangrove tree species based on UAV remote sensing images
by: Xin Wang, et al.
Published: (2024-12-01)