Manifold-Learning-Based Feature Extraction for Classification of Hyperspectral Data: A Review of Advances in Manifold Learning-Reference-Cited by-同舟云学术

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Manifold-Learning-Based Feature Extraction for Classification of Hyperspectral Data: A Review of Advances in Manifold Learning

Published:2014-01 Issue:1 Volume:31 Page:55-66
ISSN:1053-5888
Container-title:IEEE Signal Processing Magazine
language:
Short-container-title:IEEE Signal Process. Mag.

Author:

Lunga Dalton,Prasad Saurabh,Crawford Melba M.,Ersoy Okan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/79/6678221/06678226.pdf?arnumber=6678226

Cited by 227 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. Nonlinear Unmixing of Hyperspectral Images via Regularized Wasserstein Dictionary Learning;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

2. Spectral-Spatial Mamba for Hyperspectral Image Classification;Remote Sensing;2024-07-03

3. A Novel Unsupervised Domain Adaptation Transformation Reconstructed Gated Recurrent Unit Framework Considering Prediction Uncertainty for Machinery Prognostics Under Variable Lubrication Conditions;ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering;2024-06-29

4. Integration of Manifold Learning and Density Estimation for Fine-Tuned Face Recognition;Symmetry;2024-06-18

5. Hyperspectral Image Endmember Extraction Algorithm Based on Manifold Learning and Superpixel Feature Extraction;2024 6th International Conference on Communications, Information System and Computer Engineering (CISCE);2024-05-10

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