This study showcases the power of deep learning technology in automating landslides’ detection processes and provides a basis for incorporating the technique into the disaster monitoring system framework.
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
Landslides are a type of natural disaster that causes massive loss of life and property. Continuous observation of ground deformation is necessary for early warning and mitigation of risks. Interferometric Synthetic Aperture Radar (InSAR) technology facilitates large-scale, all-weather observation of ground deformation...
D. Chandran, A. N, Adhithya P. Nair et al.· International Conference Inn...· 0 citations
The results indicate that YOLOv8 achieved the highest accuracy (F-score: 0.857), followed by YOLOv5, YOLOv7, and YOLOv6, which highlight the potential of YOLO-based models for rapid and accurate landslide detection, contributing to efficient hazard assessment and disaster response efforts.
N. Chandra, Himadri Vaidya, K. Abhinav· Journal of the Geological So...· 0 citations
This study proposes a binary deep learning framework to determine whether the bridges or roads in remote sensing data have been damaged, and provides an automated method for image analysis based on remote sensing data.
Xianfeng Li, Jie-An Liang, Shi-Tao Zheng et al.· AI in Civil Engineering· 0 citations
Landslide prediction plays an important role in disaster risk reduction and protecting infrastructure and human lives when performed accurately and in a timely manner. Despite good performance, machine learning techniques are hindered by severe class imbalance in landslide datasets and the opacity of complex predictive...
Mohsin Hassan, A. Kotwal, J. Manhas et al.· Cureus Journal of Computer S...· 0 citations
A deep learning-based semantic segmentation framework using the U-Net architecture for pixel-level landslide delineation from multispectral and topographical remote sensing data and establishes a foundation for further investigation of advanced Transformer- and attention-based architectures is presented.
Neeta Bajpai, Rahul Pethe· International journal of com...· 0 citations
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