README.md

Land Use / Land Cover classification of satellite imagery without much labelled data

This repository incorporates the work of:

• Scheibenreif, Hanna, Mommert, Borth, Self-supervised Vision Transformers for Land-cover Segmentation and Classification, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2022, pp. 1422-1431

Additionally, it includes code from the following sources:

• Data handling
• SimCLR
• Swin Transformer
• Swin-Unet