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Landslide Detection Using Deep Learning and Satellite Imagery -
Comparative Analysis of Deep Learning Algorithms for Crop Type Mapping -
Application of multi-spectral indexes in monitoring temporal and spatial changes of vegetation using Modis satellite images in GEE system -
Post-earthquake road debris detection based on deep neural networks and post-event very high-resolution images -
Generating soil moisture map using radar data and GEE (Google Earth Engine) -
Classification of satellite images with vegetation based on photogrammetry and remote sensing in R programming -
Object detection based on the model developed from deep learning networks, YOLOv5+ (Pytorch0) using remote sensing images with high spatial resolution -
Analyzing the ability of maximum likelihood, support vector machine, and random forest algorithms in land use classification with the help of Google Earth ground truth data -
Analyzing changes in urban areas using images with the high spatial resolution