Consistency Self-Training Semi-Supervised Method for Road Extraction from Remote Sensing Images
Road extraction techniques based on remote sensing image have significantly advanced. Currently, fully supervised road segmentation neural networks based on remote sensing images require a significant number of densely labeled road samples, limiting their applicability in large-scale scenarios. Cons...
Saved in:
| Main Authors: | Xingjian Gu, Supeng Yu, Fen Huang, Shougang Ren, Chengcheng Fan |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-10-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/16/21/3945 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Consistency Regularization for Semi-Supervised Semantic Segmentation of Flood Regions From SAR Images
by: G. Savitha, et al.
Published: (2025-01-01) -
Semi-Supervised Object Detection for Remote Sensing Images Using Consistent Dense Pseudo-Labels
by: Tong Zhao, et al.
Published: (2025-04-01) -
SSOD-QCTR: Semi-Supervised Query Consistent Transformer for Optical Remote Sensing Image Object Detection
by: Xinyu Ma, et al.
Published: (2024-12-01) -
Training strategies for semi-supervised remote sensing image captioning
by: Qimin Cheng, et al.
Published: (2025-07-01) -
Semi-supervised tissue segmentation from histopathological images with consistency regularization and uncertainty estimation
by: G. V. S. Sudhamsh, et al.
Published: (2025-02-01)