Feature Dimensionality Reduction With L2,p-Norm-Based Robust Embedding Regression for Classification of Hyperspectral Images-Reference-Cited by-同舟云学术

Feature Dimensionality Reduction With L2,p-Norm-Based Robust Embedding Regression for Classification of Hyperspectral Images

Author:

Deng Yang-Jun¹^ORCID,Yang Meng-Long¹,Li Heng-Chao²^ORCID,Long Chen-Feng¹,Fang Kui¹,Du Qian³^ORCID

Affiliation:

1. College of Information and Intelligence, Hunan Agricultural University, Changsha, China

2. School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China

3. Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS, USA

Funder

National Natural Science Foundation of China

Hunan Provincial Key Research and Development Program

Hunan Provincial Natural Science Foundation of China

Scientific Research Fund of Hunan Provincial Education Department

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

Reference50 articles.

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3. Multi-Scale CNN with Graph-Convolutional Classifier for Classification of Hyperspectral Images;2024 2nd International Conference on Pattern Recognition, Machine Vision and Intelligent Algorithms (PRMVIA);2024-05-24