Aug 2026· Bulletin of Engineering Geology and the Environment· Vol 85· 0 citations· 37 references
TL;DR
A multi-module synergistic architecture integrating Atrous Spatial Pyramid Pooling, Squeeze-and-Excitation attention, and Path Aggregation Network with an EfficientNet-B4 encoder for automated landslide segmentation from high-resolution satellite imagery is proposed.
Results indicate that attention-based feature refinement and boundary-aware supervision can work complementarily to improve landslide segmentation while maintaining a favorable balance between segmentation performance and computational efficiency.
Chuan Jiang, Heng-Gang Zhang, Yi-Ting Wang et al.· Remote Sensing· 0 citations
Landslide detection is essential for geological disaster mitigation, yet existing deep learning methods still struggle with the high cost of global feature modeling, limited receptive fields in window-based attention, and insufficient fusion of local and global information. To address these challenges, we propose MTTNe...
Jia-Xin Song, Shu-Wen Yang, Hao Zhu et al.· IEEE Geoscience and Remote S...· 0 citations
Two improved models enhanced the accuracy of landslide identification and resistance to interference, demonstrating potential for landslide monitoring and emergency response.
N. Liang, Zhuan Li, Lei Xue et al.· Remote Sensing· 0 citations
This research introduces fusion attention vision transformer (FAViT), a novel hybrid deep learning framework for the automated rapid mapping of landslides from multitemporal Sentinel-1 synthetic aperture radar (SAR) amplitude data. A significant challenge in this domain is the need for methods that are both computation...
W. Hussain, B. Pan, S. Hussain· IEEE Journal of Selected Top...· 0 citations
The accurate segmentation of remote sensing imagery is critical for precision agriculture but challenging due to spectral complexity and ambiguous interclass boundaries. The convolutional neural networks are limited in modeling global context, while transformer-based methods incur high computational overhead. This lett...
The results show that model selection in building extraction cannot rest on a single accuracy figure, and that boundary-based metrics should govern the choice in applications where the position of the boundary is critical.
Cafer Yazıcıoğlu, Ammar Aslan· Gazi Üniversitesi Fen Biliml...· 0 citations
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