A Lightweight Remote-Sensing Image-Change Detection Algorithm Based on Asymmetric Convolution and Attention Coupling
Remote-sensing image-change detection is indispensable for land management, environmental monitoring and related applications. In recent years, breakthroughs in satellite sensor technology have generated vast volumes of data and complex scenes, presenting significant challenges for change-detection...
Saved in:
| Main Authors: | Enze Zhang, Yan Li, Haifeng Lin, Min Xia |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/13/2226 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Lightweight underwater object detection method based on multi-scale edge information selection
by: Shaobin Cai, et al.
Published: (2025-07-01) -
Efficient Gearbox Fault Diagnosis Based on Improved Multi-Scale CNN with Lightweight Convolutional Attention
by: Bin Yuan, et al.
Published: (2025-04-01) -
The Lightweight Fracture Segmentation Algorithm for Logging Images Based on Fully 3D Attention Mechanism and Deformable Convolution
by: Qishun Yang, et al.
Published: (2024-11-01) -
LCD-Net: A Lightweight Remote Sensing Change Detection Network Combining Feature Fusion and Gating Mechanism
by: Wenyu Liu, et al.
Published: (2025-01-01) -
Multi-Level Intertemporal Attention-Guided Network for Change Detection in Remote Sensing Images
by: Shuo Liu, et al.
Published: (2025-06-01)