Multiobjective band selection approach via an adaptive particle swarm optimizer for remote sensing hyperspectral images-Reference-Cited by-同舟云学术

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Multiobjective band selection approach via an adaptive particle swarm optimizer for remote sensing hyperspectral images

Published:2024-08 Issue: Volume:89 Page:101614
ISSN:2210-6502
Container-title:Swarm and Evolutionary Computation
language:en
Short-container-title:Swarm and Evolutionary Computation

Author:

Zhang Yuze,Lin Qiuzhen^ORCID,Li Lingjie,Xiao Zhijiao,Ming Zhong,Leung Victor C.M.^ORCID

Publisher

Elsevier BV

Reference51 articles.

1. Very high-resolution remote sensing: Challenges and opportunities [point of view];Benediktsson;Proc. IEEE,2012

2. Hyperspectral remote sensing data analysis and future challenges;Bioucas-Dias;IEEE Geosci. Remote Sens. Mag.,2013

3. Dimensionality reduction and classification of hyperspectral images using ensemble discriminative local metric learning;Dong;IEEE Trans. Geosci. Remote Sens.,2017

4. A new spatial–spectral feature extraction method for hyperspectral images using local covariance matrix representation;Fang;IEEE Trans. Geosci. Remote Sens.,2018

5. Feature extraction for hyperspectral imagery: The evolution from shallow to deep: Overview and toolbox;Rasti;IEEE Geosci. Remote Sens. Mag.,2020

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. Two New Bio-Inspired Particle Swarm Optimisation Algorithms for Single-Objective Continuous Variable Problems Based on Eavesdropping and Altruistic Animal Behaviours;Biomimetics;2024-09-05

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