An Effective Feature Extraction Approach Based on Spectral-Gabor Space Discriminant Analysis for Hyperspectral Image
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software
Link
https://link.springer.com/content/pdf/10.1007/s11063-021-10665-w.pdf
Reference54 articles.
1. Kumar B, Dikshit O, Gupta A et al (2020) Feature extraction for hyperspectral image classification: a review [J]. International Journal of Remote Sensing 41(16):6248–6287
2. Jia X, Kuo BC, Crawford MM (2013) Feature mining for hyperspectral image classification[J]. Proc IEEE 101(3):676–697
3. Hosseini SA, Ghassemian H (2016) Hyperspectral Data Feature Extraction Using Rational Function Curve Fitting[J]. Int J Pattern Recognit Artif Intell 30(01):1650001. https://doi.org/10.1142/S0218001416500014
4. Hosseini SA, Ghassemian H (2016) Rational function approximation for feature reduction in hyperspectral data[J]. Remote Sensing Letters 2:101–110
5. Imani M, Ghassemian H (2017) High-dimensional image data feature extraction by double discriminant embedding[J]. Pattern Anal Appl 20(2):473–484
Cited by 2 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. Hyperspectral Image Classification Based on 3D–2D Hybrid Convolution and Graph Attention Mechanism;Neural Processing Letters;2024-03-20
2. Hyperspectral Image Classification Based on 3D-2D Hybrid Convolution and Graph Attention Mechanism;2023-07-18
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