Exploring Hybrid Contrastive Learning and Scene-to-Label Information for Multilabel Remote Sensing Image Classification-Reference-Cited by-同舟云学术

Exploring Hybrid Contrastive Learning and Scene-to-Label Information for Multilabel Remote Sensing Image Classification

Published:2024 Issue: Volume:62 Page:1-14
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Song Tiecheng¹^ORCID,Bai Shufen²^ORCID,Yang Feng²^ORCID,Gao Chenqiang³^ORCID,Chen Haonan⁴^ORCID,Li Jun⁵^ORCID

Affiliation:

1. School of Communications and Information Engineering and the Institute for Advanced Sciences, Chongqing University of Posts and Telecommunications, Chongqing, China

2. School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China

3. School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China

4. Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, CO, USA

5. School of Computer Science and Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Natural Science Foundation of Chongqing, China

China Postdoctoral Science Foundation

Chongqing Postdoctoral Research

Funding of the Institute for Advanced Sciences, Chongqing University of Posts and Telecommunications,

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/36/10354519/10580951.pdf?arnumber=10580951

Reference57 articles.

1. Dimensionality Reduction of Hyperspectral Imagery Based on Spatial–Spectral Manifold Learning

2. A Coarse-to-Fine Semi-Supervised Change Detection for Multispectral Images

3. Hybrid Feature Aligned Network for Salient Object Detection in Optical Remote Sensing Imagery

4. Remote Sensing Scene Classification by Unsupervised Representation Learning

5. SPNet: Siamese-Prototype Network for Few-Shot Remote Sensing Image Scene Classification