Fine tuning CLIP with Remote Sensing (Satellite) images and captions

The article discusses the fine-tuning of the CLIP (Contrastive Language–Image Pre-training) model using remote sensing satellite images and their corresponding captions. This adaptation allows CLIP to better understand and classify satellite imagery, improving its performance on tasks such as land cover classification and change detection. The approach demonstrates significant gains in accuracy on benchmark datasets, making it a valuable method for practitioners working with satellite data in AI applications.