A Novel Hyperspectral Image Classification Model Using Bole Convolution With Three-Direction Attention Mechanism: Small Sample and Unbalanced Learning-Reference-Cited by-同舟云学术

A Novel Hyperspectral Image Classification Model Using Bole Convolution With Three-Direction Attention Mechanism: Small Sample and Unbalanced Learning

Published:2023 Issue: Volume:61 Page:1-17
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Cai Weiwei¹^ORCID,Ning Xin²^ORCID,Zhou Guoxiong³,Bai Xiao⁴^ORCID,Jiang Yizhang¹^ORCID,Li Wei⁵^ORCID,Qian Pengjiang¹^ORCID

Affiliation:

1. School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China

2. Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China

3. School of Computer Information and Engineering, Central South University of Forestry and Technology, Changsha, China

4. School of Computer Science and Engineering, Beihang University, Beijing, China

5. School of Information and Electronics, Beijing Institute of Technology, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/09875214.pdf?arnumber=9875214

Reference42 articles.

1. An overview on spectral and spatial information fusion for hyperspectral image classification: Current trends and challenges

2. Three-dimensional densely connected convolutional network for hyperspectral remote sensing image classification

3. Spectral-Spatial Unified Networks for Hyperspectral Image Classification

4. Spectral–Spatial Classification of Hyperspectral Imagery with 3D Convolutional Neural Network

5. A Quantum Annealer for Subset Feature Selection and the Classification of Hyperspectral Images

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