Research Article
Remote Sensing Image Analysis Based on Transfer Learning: A Survey
@INPROCEEDINGS{10.1007/978-3-030-19086-6_45, author={Ruowu Wu and Yuyao Li and Hui Han and Xiang Chen and Yun Lin}, title={Remote Sensing Image Analysis Based on Transfer Learning: A Survey}, proceedings={Advanced Hybrid Information Processing. Second EAI International Conference, ADHIP 2018, Yiyang, China, October 5-6, 2018, Proceedings}, proceedings_a={ADHIP}, year={2019}, month={5}, keywords={Transfer learning Remote sensing image Target detection Target recognition Image classification}, doi={10.1007/978-3-030-19086-6_45} }- Ruowu Wu
Yuyao Li
Hui Han
Xiang Chen
Yun Lin
Year: 2019
Remote Sensing Image Analysis Based on Transfer Learning: A Survey
ADHIP
Springer
DOI: 10.1007/978-3-030-19086-6_45
Abstract
Transfer learning is a new topic in machine learning. Psychology holds that the process of learning knowledge from one to the other is a process of transfer learning. Transfer learning is different from machine learning which has to satisfy the following two conditions: (1) The training samples and testing samples must be in the same feature spaces. (2) There must be enough training samples to obtain an excellent training model. Because of the ability of transfer learning to solve problems with small samples and the ability to use historical auxiliary models to solve new problems, it is introduced in remote sensing image analysis. At first, this paper introduces some basic knowledge of transfer learning and enumerates some basic research examples. The research content of this paper mainly involves several problems based on transfer learning, such as target detection and recognition, image classification, etc.