Water extraction from optical high-resolution remote sensing imagery: a multi-scale feature extraction network with contrastive learning

Author:

Liu Bo1,Du Shihong1,Bai Lubin1,Ouyang Song1,Wang Haoyu1,Zhang Xiuyuan1

Affiliation:

1. Institute of Remote Sensing and GIS, Peking University, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Reference47 articles.

1. Bachman, P., R. D. Hjelm, and W. Buchwalter. 2019. “Learning Representations by Maximizing Mutual Information Across Views.” Paper Presented at the Conference on Neural Information Processing Systems, Vancouver, CANADA, December 08-14.

2. Domain Adaptation for Remote Sensing Image Semantic Segmentation: An Integrated Approach of Contrastive Learning and Adversarial Learning

3. Chaitanya, K., E. Erdil, N. Karani, and K. Ender. 2020. “Contrastive Learning of Global and Local Features for Medical Image Segmentation with Limited Annotation.” Paper Presented at the Conference on Neural Information Processing Systems, Vancouver, CANADA, December 02-08.

4. Extraction of Water Information Based on China-Made GF-1 Remote Sensing Image;Chen W. Q.;Resources Science,2015

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