Probabilistic Collaborative Representation Based Ensemble Learning for Classification of Wetland Hyperspectral Imagery-Reference-Cited by-同舟云学术

Probabilistic Collaborative Representation Based Ensemble Learning for Classification of Wetland Hyperspectral Imagery

Published:2023 Issue: Volume:61 Page:1-17
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Su Hongjun¹^ORCID,Shao Fu¹,Gao Yihan¹,Zhang Huihui¹,Sun Weiwei²^ORCID,Du Qian³^ORCID

Affiliation:

1. School of Earth Sciences and Engineering and the Jiangsu Province Engineering Research Center of Water Resources and Environment Assessment Using Remote Sensing, Hohai University, Jiangning, China

2. Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo, China

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

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10103545.pdf?arnumber=10103545

Reference62 articles.

1. A simple and robust wetland classification approach by using optical indices, unsupervised and supervised machine learning algorithms

2. Learning with Kernels

3. Central Attention Network for Hyperspectral Imagery Classification

4. Multiple Kernel Learning for Sparse Representation-Based Classification

5. Multi-Layer Global Spectral-Spatial Attention Network for Wetland Hyperspectral Image Classification

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