Techniques for deep learning with satellite & aerial imagery
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Updated
Oct 20, 2024
Techniques for deep learning with satellite & aerial imagery
GDAL is an open source MIT licensed translator library for raster and vector geospatial data formats.
Long list of geospatial tools and resources
Framework agnostic sliced/tiled inference + interactive ui + error analysis plots
🛰️ List of satellite image training datasets with annotations for computer vision and deep learning
A Python package for interactive geospatial analysis and visualization with Google Earth Engine.
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
An open source library and framework for deep learning on satellite and aerial imagery.
List of datasets, codes, and contests related to remote sensing change detection
A collection of 360+ Jupyter Python notebook examples for using Google Earth Engine with interactive mapping
A curated list of awesome tools, tutorials, code, projects, links, stuff about Earth Observation, Geospatial Satellite Imagery
Search and download Copernicus Sentinel satellite images
A curated list of Google Earth Engine resources
An advanced geospatial data analysis platform
A collection of 300+ Python examples for using Google Earth Engine in QGIS
A ready-to-use curated list of Spectral Indices for Remote Sensing applications.
GRASS GIS - free and open-source geospatial processing engine
A review of change detection methods, including codes and open data sets for deep learning. From paper: change detection based on artificial intelligence: state-of-the-art and challenges.
Community Datasets added by users and made available for use at large
This repo is the codebase for our team to participate in DOTA related competitions, including rotation and horizontal detection.
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