An Ultralightweight Hybrid CNN Based on Redundancy Removal for Hyperspectral Image Classification-Reference-Cited by-同舟云学术

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An Ultralightweight Hybrid CNN Based on Redundancy Removal for Hyperspectral Image Classification

Published:2024 Issue: Volume:62 Page:1-12
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Ma Xiaohu¹^ORCID,Wang Wuli¹^ORCID,Li Wei²^ORCID,Wang Jianbu³,Ren Guangbo³,Ren Peng¹^ORCID,Liu Baodi⁴^ORCID

Affiliation:

1. College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao, China

2. School of Information and Electronics, Beijing Institute of Technology, Beijing, China

3. Laboratory of Marine Physics and Remote Sensing, First Institute of Oceanography, Ministry of Natural Resources, Qingdao, China

4. College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China

Funder

Funds of the National Natural Science Foundation of China

Key Laboratory of Land Satellite Remote Sensing Application, Ministry of Natural Resources of the People’s Republic of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10410870.pdf?arnumber=10410870

Reference34 articles.

1. Estimating Soil Salinity Under Various Moisture Conditions: An Experimental Study

2. Deep learning classifiers for hyperspectral imaging: A review

3. Medical hyperspectral imaging: a review

4. Kernel-based methods for hyperspectral image classification

5. Classification of hyperspectral remote sensing images with support vector machines

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Lightweight and Lifelong Hyperspectral Image Classification via Attention-Based Reservoir Computing;IEEE Transactions on Geoscience and Remote Sensing;2024

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