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This repository is a comprehensive, curated collection of deep learning techniques and best practices specifically applied to satellite and aerial imagery. It covers everything from preprocessing and annotation to model architectures and open datasets. The guide includes code snippets, links to research papers, and hands-on tools, making it valuable for researchers, engineers, and enthusiasts working in remote sensing and geospatial AI.
Features
- Covers model architectures for geospatial tasks
- Includes preprocessing and annotation methods
- Links to datasets and benchmarks
- Focuses on segmentation, detection, and classification
- Summarizes key papers and implementations
- Continuously updated with new tools and practices
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Deep Learning FrameworksLicense
Apache License V2.0Follow Techniques
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