An efficient dual feature fusion model of feature extraction for hyperspectral images-Reference-Cited by-同舟云学术

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An efficient dual feature fusion model of feature extraction for hyperspectral images

Published:2023-07-18 Issue:14 Volume:44 Page:4217-4238
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Wang Xianyue¹,Qian Longxia¹^ORCID,Shi Jian²,Hong Mei²,Cao Jinde³⁴

Affiliation:

1. School of Science, Nanjing University of Posts and Telecommunications, Nanjing, China

2. College of Meteorology and Oceanography, National University of Defense Technology, Changsha, China

3. School of Mathematics, Southeast University, Nanjing, China

4. Jiangsu Provincial Key Laboratory of Networked Collective Intelligence, Southeast University, Nanjing, China

Funder

the Natural Science Foundation of Hunan Province under Grant

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2023.2234091

Reference43 articles.

1. Randomized Algorithms for Computation of Tucker Decomposition and Higher Order SVD (HOSVD)

2. Object recognition with adaptive Gabor features

3. Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review

4. Kernel Low-Rank Entropic Component Analysis for Hyperspectral Image Classification

5. UAV-hyperspectral imaging of spectrally complex environments

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. An Efficient and Adaptive Reconstructive Homogeneous Block-Based Local Tensor Robust PCA for Feature Extraction of Hyperspectral Images;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

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