Deep learning with satellite imagery and geospatial data

This course provides an introduction to Deep Learning applied to geospatial and remotely sensed data. Currently there are five exercises available:

1. temperature prediction and introduction to DNN notebook for intro to dnn
2. introduction to image classification and CNN using CIFAR 10 notebook for intro to cnn
3. land cover scene image classification with Sentinel 2: under development notebook for sentinel2_land_cover_image_classification
4. introduction to semantic classification with remotely sensed data: building mapping notebook for intro to semantic_segmentation
5. introduction to transfer for image classification notebook for intro to transfer_learning_classification
6. 3D hybrid CNN for hyperspectral classification notebook for hyperspectral_application_in_deep_learning

Upcoming exercises:

• deep learning flood mapping with sentinel 1
• object detection yolo8