Consecutive Pretraining: A Knowledge Transfer Learning Strategy with Relevant Unlabeled Data for Remote Sensing Domain. (arXiv:2207.03860v2 [cs.CV] UPDATED)

Currently, under supervised learning, a model pretrained by a large-scale
nature scene dataset and then fine-tuned on a few specific task labeling data
is the paradigm that has dominated the knowledge transfer learning. It has
reached the status of consensus solution for task-aware model training in
remote sensing domain (RSD). Unfortunately, due to different categories of
imaging data and stiff challenges of data annotation, there is not a large
enough and uniform remote sensing dataset to support large-scale pretraining in …

arxiv data knowledge remote sensing strategy transfer transfer learning