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Detection and characterization of active landslides with multisource SAR data and remote sensing in western Guizhou, China

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Integration of Sentinel-1 and ALOS/PALSAR-2 SAR datasets for mapping active landslides along the Jinsha River corridor, China

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Comparison of Machine Learning Methods for Potential Active Landslide Hazards Identification with Multi-Source Data

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Convolutional neural networks applied to semantic segmentation of landslide scars

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Matrix SegNet: A Practical Deep Learning Framework for Landslide Mapping from Images of Different Areas with Different Spatial Resolutions

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Active-Learning Approaches for Landslide Mapping Using Support Vector Machines

(2021) Zhihao Wang et al.   Remote Sensing

Evaluation of Semantic Segmentation Methods for Land Use with Spectral Imaging Using Sentinel-2 and PNOA Imagery

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Average-DInSAR method for unstable escarpments detection induced by underground coal mining

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An Efficient Lightweight Neural Network for Remote Sensing Image Change Detection

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Deep Learning Meets SAR: Concepts, models, pitfalls, and perspectives

(2021) Xiao Xiang Zhu et al.   IEEE Geoscience and Remote Sensing Magazine

Landslide detection from an open satellite imagery and digital elevation model dataset using attention boosted convolutional neural networks

(2020) Shunping Ji et al.   Landslides

Mapping Landslides on EO Data: Performance of Deep Learning Models vs. Traditional Machine Learning Models

(2020) Nikhil Prakash et al.   Remote Sensing

Research on Post-Earthquake Landslide Extraction Algorithm Based on Improved U-Net Model

(2020) Peng Liu et al.   Remote Sensing

Landslide identification using machine learning

(2020) Haojie Wang et al.   Geoscience Frontiers

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(2020) Wenwen Qi et al.   Remote Sensing

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Machine learning for landslides prevention: a survey

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Automatic Extraction of Seismic Landslides in Large Areas with Complex Environments Based on Deep Learning: An Example of the 2018 Iburi Earthquake, Japan

(2020) Pengfei Zhang et al.   Remote Sensing

Evaluation of Different Machine Learning Methods and Deep-Learning Convolutional Neural Networks for Landslide Detection

(2019) Omid Ghorbanzadeh et al.   Remote Sensing

Comparison of convolutional neural networks for landslide susceptibility mapping in Yanshan County, China

(2019) Yi Wang et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Deep learning in remote sensing applications: A meta-analysis and review

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Landslide detection based on contour-based deep learning framework in case of national scale of Nepal in 2015

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Deep Residual Shrinkage Networks for Fault Diagnosis

(2019) Minghang Zhao et al.   IEEE Transactions on Industrial Informatics

A comparative analysis of pixel- and object-based detection of landslides from very high-resolution images

(2018) Ren N. Keyport et al.   International Journal of Applied Earth Observation and Geoinformation

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(2018) Chaoying Zhao et al.   Remote Sensing

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

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Object-Oriented Landslide Mapping Using ZY-3 Satellite Imagery, Random Forest and Mathematical Morphology, for the Three-Gorges Reservoir, China

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A tutorial on synthetic aperture radar

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Landslide inventory maps: New tools for an old problem

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Object-Oriented Change Detection for Landslide Rapid Mapping

(2011) Ping Lu et al.   IEEE Geoscience and Remote Sensing Letters

Landslide susceptibility mapping based on Support Vector Machine: A case study on natural slopes of Hong Kong, China

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