Classification of hyperspectral images using a propagation filter and convolutional neural network-Reference-Cited by-同舟云学术

Classification of hyperspectral images using a propagation filter and convolutional neural network

Published:2022-02-16 Issue:5 Volume:13 Page:429-440
ISSN:2150-704X
Container-title:Remote Sensing Letters
language:en
Short-container-title:Remote Sensing Letters

Author:

Yan Qin¹,Wang Ning²,Jiang Xinwei¹,Cai Yaoming¹,Zhang Yongshan¹,Liu Xiaobo³,Cai Zhihua¹

Affiliation:

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

2. Changjiang Survey Planning Design and Research Co., Ltd, Wuhan, Hubei, China

3. School of Automation, and Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, China University of Geosciences, Wuhan, China

Funder

National Natural Science Foundation of China

National Nature Science Foundation of Hubei Province

Science and Technology Project of Department of Natural Resources, Hubei Province

Open Research Project of The Hubei Key Laboratory of Intelligent Geo-Information Processing

Publisher

Informa UK Limited

Subject

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

Link

https://www.tandfonline.com/doi/pdf/10.1080/2150704X.2021.1957175

Reference16 articles.

1. BS-Nets: An End-to-End Framework for Band Selection of Hyperspectral Image

2. Propagated image filtering

3. Spectral-Spatial Feature Extraction of Hyperspectral Images Based on Propagation Filter

4. Hyperspectral Images Classification With Gabor Filtering and Convolutional Neural Network

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