| 🔥 Deep learning Workshop for Satellite Imagery - Data Processing (Part 1/3) |
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| 🔥 Deep learning Workshop for Satellite Imagery - Training & Prediction (Part 2/3) |
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- Google Colab Notebook - Data Processing (Part 1)
- Google Colab Notebook - Deep Learing (Part 2 Base)
- Google Colab Notebook - Deep Learing (Part 2 with Local Diagnostics)
- Slide Deck used during Workshop (Please see the files in same folder)
- Dubai Segmentation Dataset Kaggle - https://www.kaggle.com/datasets/humansintheloop/semantic-segmentation-of-aerial-imagery
- Dubai Segmentation Dataset Home: https://humansintheloop.org/resources/datasets/semantic-segmentation-dataset-2/
- Super Lage (38GB) Space Satellite Image Daset - https://spacenet.ai/sn6-challenge/
- Segmentation Model for Loss Metrics: https://github.com/qubvel/segmentation_models
- GitHub Project (Another) - https://github.com/ayushdabra/dubai-satellite-imagery-segmentation
- Model Visualization: https://github.com/lutzroeder/netron
- Activation and Gradient Output- https://github.com/philipperemy/keract
- https://medium.com/@Chinmay_Paranjape/satellite-imagery-segmentation-using-u-net-4ec7f265ddbe
- https://medium.com/@fractal.ai/understanding-satellite-image-for-geo-spatial-deep-learning-a1a7dee2f2de
- https://github.com/ChinmayParanjape/Satellite-imagery-segmentation-using-U-NET
- https://medium.com/sentinel-hub/how-to-normalize-satellite-images-for-deep-learning-d5b668c885af
- https://medium.com/gsi-technology/a-beginners-guide-to-segmentation-in-satellite-images-9c00d2028d52