Robust multi‐view representation for spatial–spectral domain in application of hyperspectral image classification-Reference-Cited by-同舟云学术

Robust multi‐view representation for spatial–spectral domain in application of hyperspectral image classification

Published:2018-11-23 Issue:2 Volume:13 Page:90-96
ISSN:1751-9640
Container-title:IET Computer Vision
language:en
Short-container-title:IET Computer Vision

Author:

Li Yanshan¹²,Wang Xianchen¹³^ORCID,Huang Qinghua⁴^ORCID,Hu Xiaohui⁵,Xie Weixin¹

Affiliation:

1. ATR National Key Laboratory of Defense TechnologyShenzhen UniversityShenzhenPeople's Republic of China

2. Guangdong Key Laboratory of Intelligent Information ProcessingCollege of Information Engineering, Shenzhen UniversityShenzhenPeople's Republic of China

3. School of Electronic and Communication EngineeringShenzhen PolytechnicShenzhenPeople's Republic of China

4. The School of Mechanical Engineering, and Center for OPTical IMagery Analysis and Learning (OPTIMAL)Northwestern Polytechnical UniversityPeople's Republic of China

5. School of Physics and Telecommunication EngineeringSouth China Normal UniversityGuangzhouPeople's Republic of China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Guangzhou Science and Technology Program key projects

Publisher

Institution of Engineering and Technology (IET)

Subject

Computer Vision and Pattern Recognition,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-cvi.2018.5112

Reference33 articles.

1. Classification of hyperspectral remote sensing images with support vector machines

2. Semisupervised hyperspectral image segmentation using multinomial logistic regression with active learning;Li J.;IEEE Trans. Geosci. Remote Sens.,2010

3. Hyperspectral Image Classification Using Dictionary-Based Sparse Representation

4. Classification of Hyperspectral Images by Exploiting Spectral–Spatial Information of Superpixel via Multiple Kernels

5. Interest Points for Hyperspectral Image Data

Cited by 3 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. High Spatial Resolution Remote Sensing Data Classification Method Based on Spectrum Sharing;Scientific Programming;2021-12-20

2. CNN‐combined graph residual network with multilevel feature fusion for hyperspectral image classification;IET Computer Vision;2021-10-06

3. CNN-based salient features in HSI image semantic target prediction;Connection Science;2019-08-05