Self-Supervised Learning in Remote Sensing: A review
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) · Technical University of Munich · +1 more institution
Abstract
In deep learning research, self-supervised learning (SSL) has received great attention, triggering interest within both the computer vision and remote sensing communities. While there has been big success in computer vision, most of the potential of SSL in the domain of Earth observation remains locked. In this article, we provide an introduction to and a review of the concepts and latest developments in SSL for computer vision in the context of remote sensing. Further, we provide a preliminary benchmark of modern SSL algorithms on popular remote sensing datasets, verifying the potential of SSL in remote sensing and providing an extended study on data augmentations. Finally, we identify a list of promising…
Citation impact
- FWCI
- 30.96
- Percentile
- 100%
- References
- 293
Authors
5- YWYi WangCorresponding
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR), Technical University of Munich
- CMConrad M Albrecht
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR), European Severe Storms Laboratory
- NANassim Ait Ali Braham
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR), Technical University of Munich
- LMLichao Mou
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)
- XXXiao Xiang Zhu
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)
Topics & keywords
- Computer science
- Benchmark (surveying)
- Context (archaeology)
- Domain (mathematical analysis)
- Deep learning
- Remote sensing
- Artificial intelligence
- Data science