A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sensing images

A deeply supervised image fusion network (IFN) is proposed for change detection in high resolution bi-temporal remote sensing images and outperforms four benchmark methods derived from the literature, by returning changed areas with complete boundaries and high internal compactness compared to the state-of-the-art methods.