A Trusted Generative-Discriminative Joint Feature Learning Framework for Remote Sensing Image Classification-Reference-Cited by-同舟云学术

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A Trusted Generative-Discriminative Joint Feature Learning Framework for 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:

Si Lingyu¹,Dong Hongwei¹^ORCID,Qiang Wenwen¹^ORCID,Song Zeen¹^ORCID,Du Bo²^ORCID,Yu Junzhi³^ORCID,Sun Fuchun⁴^ORCID

Affiliation:

1. Science and Technology on Integrated Information System Laboratory, Institute of Software, Chinese Academy of Sciences, Beijing, China

2. Hubei Luojia Laboratory, National Engineering Research Center for Multimedia Software, School of Computer Science, Wuhan University, Wuhan, China

3. College of Engineering, Peking University, Beijing, China

4. Department of Computer Science and Technology, Tsinghua University, Beijing, China

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10356128.pdf?arnumber=10356128

Reference80 articles.

1. Information mining in remote sensing image archives: system concepts

2. Large-Scale Remote Sensing Image Retrieval by Deep Hashing Neural Networks

3. Exploring Models and Data for Remote Sensing Image Caption Generation

4. A survey of image classification methods and techniques for improving classification performance

5. Bag-of-visual-words and spatial extensions for land-use classification

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