A novel self‐supervised ensemble learning framework for land use and land cover classification of polarimetric synthetic aperture radar images
Mohsen Darvishnezhad,
Mohammad Ali Sebt
Abstract:Classification with a few samples of training set has been a longstanding issue in the field of polarimetric synthetic aperture radar (PolSAR) image analysis and processing. Aiming at the small number of training samples of the PolSAR image classification task, a novel Self‐Supervised Ensemble Learning Framework (SSELF) is designed. The designed SSELF can automatically extract PolSAR features conducive to PolSAR image classification with a small number of training samples. In addition, it can significantly dec… Show more
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.