UCrack-DA: A Multi-Scale Unsupervised Domain Adaptation Method for Surface Crack Segmentation
Surface cracks serve as early warning signals for potential geological hazards, and their precise segmentation is crucial for disaster risk assessment. Due to differences in acquisition conditions and the diversity of crack morphology, scale, and surface texture, there is a significant domain shift...
Saved in:
| Main Authors: | Fei Deng, Shaohui Yang, Bin Wang, Xiujun Dong, Siyuan Tian |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/12/2101 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Region and Sample Level Domain Adaptation for Unsupervised Infrared Target Detection in Aerial Remote Sensing Images
by: Lianmeng Jiao, et al.
Published: (2025-01-01) -
Multi-Granularity Domain-Adaptive Teacher for Unsupervised Remote Sensing Object Detection
by: Fang Fang, et al.
Published: (2025-05-01) -
TPDTNet: Two-Phase Distillation Training for Visible-to-Infrared Unsupervised Domain Adaptive Object Detection
by: Siyu Wang, et al.
Published: (2025-01-01) -
A UAV Based Concrete Crack Detection and Segmentation Using 2-Stage Convolutional Network with Transfer Learning
by: Joses Sorilla, et al.
Published: (2024-09-01) -
Concrete Bridge Crack Detection Using Unmanned Aerial Vehicles and Image Segmentation
by: Yanli Chen, et al.
Published: (2025-06-01)