A mixture generative adversarial network with category multi-classifier for hyperspectral image classification-Reference-Cited by-同舟云学术

A mixture generative adversarial network with category multi-classifier for hyperspectral image classification

Published:2020-09-22 Issue:11 Volume:11 Page:983-992
ISSN:2150-704X
Container-title:Remote Sensing Letters
language:en
Short-container-title:Remote Sensing Letters

Author:

Li Hengchao¹,Wang Weiye¹,Ye Shaohui¹,Deng Yangjun¹,Zhang Fan²^ORCID,Du Qian³

Affiliation:

1. School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China

2. College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China

3. Department of Electrical and Computer Engineering, Mississippi State University, Starkville, USA

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Earth and Planetary Sciences (miscellaneous)

Link

https://www.tandfonline.com/doi/pdf/10.1080/2150704X.2020.1804641

Reference18 articles.

1. Deep Learning-Based Classification of Hyperspectral Data

2. Nearest neighbor pattern classification

3. Patch Tensor-Based Multigraph Embedding Framework for Dimensionality Reduction of Hyperspectral Images

4. Goodfellow, I., J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio. 2014. “Generative Adversarial Nets.” Advances in Neural Information Processing Systems. http://papers.nips.cc/paper/5423-generative-adversarial-nets.pdf

5. Investigation of the random forest framework for classification of hyperspectral data

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