Related references
Note: Only part of the references are listed.Landslide detection by deep learning of non-nadiral and crowdsourced optical images
Filippo Catani
LANDSLIDES (2021)
Landslide failures detection and mapping using Synthetic Aperture Radar: Past, present and future
Alessandro Cesare Mondini et al.
EARTH-SCIENCE REVIEWS (2021)
Landslides induced by the 2010 Chile megathrust earthquake: a comprehensive inventory and correlations with geological and seismic factors
Alejandra Serey et al.
LANDSLIDES (2019)
Sentinel-1 SAR Amplitude Imagery for Rapid Landslide Detection
Alessandro C. Mondini et al.
REMOTE SENSING (2019)
Coseismic landslides triggered by the 2018 Hokkaido, Japan (Mw 6.6), earthquake: spatial distribution, controlling factors, and possible failure mechanism
Fengrui Wang et al.
LANDSLIDES (2019)
Characteristics of landslides caused by the 2018 Hokkaido Eastern Iburi Earthquake
Nobutomo Osanai et al.
LANDSLIDES (2019)
Landslides triggered by multiple earthquakes: insights from the 2018 Lombok (Indonesia) events
M. F. Ferrario
NATURAL HAZARDS (2019)
Evaluation of Different Machine Learning Methods and Deep-Learning Convolutional Neural Networks for Landslide Detection
Omid Ghorbanzadeh et al.
REMOTE SENSING (2019)
Geological characteristics of landslides triggered by the 2016 Kumamoto earthquake in Mt. Aso volcano, Japan
Kun Song et al.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT (2019)
Landslides Triggered by the 2016 Mw 7.8 Pedernales, Ecuador Earthquake: Correlations with ESI-07 Intensity, Lithology, Slope and PGA-h
Kervin Chunga et al.
GEOSCIENCES (2019)
A review of statistically-based landslide susceptibility models
Paola Reichenbach et al.
EARTH-SCIENCE REVIEWS (2018)
Landslides by the 2018 Hokkaido Iburi-Tobu Earthquake on September 6
Hiromitsu Yamagishi et al.
LANDSLIDES (2018)
Satellite-based emergency mapping using optical imagery: experience and reflections from the 2015 Nepal earthquakes
Jack G. Williams et al.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES (2018)
Rainfall-induced landslide susceptibility assessment at the Chongren area (China) using frequency ratio, certainty factor, and index of entropy
Haoyuan Hong et al.
GEOCARTO INTERNATIONAL (2017)
Object Recognition in Aerial Images Using Convolutional Neural Networks
Matija Radovic et al.
JOURNAL OF IMAGING (2017)
ImageNet Classification with Deep Convolutional Neural Networks
Alex Krizhevsky et al.
COMMUNICATIONS OF THE ACM (2017)
Landslide susceptibility mapping based on landslide history and analytic hierarchy process (AHP)
Dimitrios Myronidis et al.
NATURAL HAZARDS (2016)
Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions
Adam M. Wilson et al.
PLOS BIOLOGY (2016)
Classification and Segmentation of Satellite Orthoimagery Using Convolutional Neural Networks
Martin Langkvist et al.
REMOTE SENSING (2016)
Landslide susceptibility estimation by random forests technique: sensitivity and scaling issues
F. Catani et al.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES (2013)
Satellite image analysis for disaster and crisis-management support
Stefan Voigt et al.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2007)