Learning latent local manifold embeddings for hyperspectral feature extraction-Reference-Cited by-同舟云学术

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Learning latent local manifold embeddings for hyperspectral feature extraction

Published:2022-08-29 Issue:03 Volume:16 Page:
ISSN:1931-3195
Container-title:Journal of Applied Remote Sensing
language:
Short-container-title:J. Appl. Rem. Sens.

Author:

Yu Wenbo¹,Zhang Miao²,Huang He¹,Shen Yi²,Shen Gangxiang¹

Affiliation:

1. Soochow University, School of Electronics and Information Engineering, Department of Electronics and Information Engineering, Suzhou, China

2. Harbin Institute of Technology, School of Astronautics, Department of Control Science and Engineering, Harbin, China

Publisher

SPIE-Intl Soc Optical Eng

Subject

General Earth and Planetary Sciences

Reference55 articles.

1. Superpixel-based 3D deep neural networks for hyperspectral image classification

2. A general framework for transfer sparse subspace learning

3. Hyperspectral Image Classification With Rotation Random Forest Via KPCA

4. Radiometric quality improvement of hyperspectral remote sensing images: a technical tutorial on variational framework

5. Hyperspectral remote sensing in lithological mapping, mineral exploration, and environmental geology: an updated review

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