A Transfer Learning Approach for Landslide Semantic Segmentation Based on Visual Foundation Model
Landslides are one of the most destructive natural disasters in the world, threatening human life and safety. With excellent performance as a foundation model for image segmentation, the segment anything model (SAM) has provided a novel paradigm for semantic segmentation research. However, the lack...
Saved in:
| Main Authors: | Changhong Hou, Junchuan Yu, Daqing Ge, Liu Yang, Laidian Xi, Yunxuan Pang, Yi Wen |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10962290/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Integration of geospatial foundation models in unsupervised change detection workflows for landslide identification
by: Julia Anna Leonardi, et al.
Published: (2025-08-01) -
Applications and Advancements of Spaceborne InSAR in Landslide Monitoring and Susceptibility Mapping: A Systematic Review
by: Yusen Cheng, et al.
Published: (2025-03-01) -
Landslide and landslide-talus processes on the roads of the Рrigorodny district and the urban district of Vladikavkaz (the Republic of North Ossetia – Alania)
by: V. V. Razumov, et al.
Published: (2025-01-01) -
A Landslide Susceptibility Mapping Method Based on Geographic Information System and Data Enhancement Techniques: A Case Study of Guangzhou City, China
by: Long Chen, et al.
Published: (2024-12-01) -
A mathematical approach for assessing landslide vulnerability
by: Hernan Eduardo Martinez-Carvajal, et al.
Published: (2018-10-01)