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This page lists resources for performing deep learning on satellite imagery. To a lesser extent classical Machine learning (e.g. random forests) are also discussed, as are classical image processing techniques. Note there is a huge volume of academic literature published on these topics, and this repository does not seek to index them all but rather list approachable resources with published code that will benefit both the research and developer communities. If you find this work useful please give it a star and consider sponsoring it. You can also follow me on Twitter and LinkedIn where I aim to post frequent updates on my new discoveries, and I have created a dedicated group on LinkedIn. I have also started a blog here and have published a post on the history of this repository called Dissecting the satellite-image-deep-learning repo.
Features
- Object detection with rotated bounding boxes
- Object detection enhanced by super resolution
- Autoencoders, dimensionality reduction, image embeddings & similarity search
- Self-supervised, unsupervised & contrastive learning
- Oil storage tank detection & oil spills
- Deep learning packages, frameworks & projects
Project Samples
