Structure-Adaptive Convolutional Neural Network for Hyperspectral Image Classification-Reference-Cited by-同舟云学术

Structure-Adaptive Convolutional Neural Network for Hyperspectral Image Classification

Published:2023 Issue: Volume:61 Page:1-16
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Jia Sen¹^ORCID,Bi Dongsheng¹^ORCID,Liao Jianhui¹,Jiang Shuguo²,Xu Meng¹^ORCID,Zhang Shuyu¹^ORCID

Affiliation:

1. College of Computer Science and Software Engineering, the Guangdong–Hong Kong–Macau Joint Laboratory for Smart Cities, and the Key Laboratory for Geo-Environmental Monitoring of Coastal Zone, Ministry of Natural Resources, Shenzhen University, Shenzhen, China

2. School of Computer Science, Wuhan University, Wuhan, China

Funder

National Natural Science Foundation of China

Department of Education of Guangdong Province

Basic and Applied Basic Research Foundation of Guangdong Province

Shenzhen Science and Technology Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10288511.pdf?arnumber=10288511

Reference55 articles.

1. Multiple Kernel Learning for Hyperspectral Image Classification: A Review

2. Contour Structural Profiles: An Edge-Aware Feature Extractor for Hyperspectral Image Classification

3. A 3-D Gabor Phase-Based Coding and Matching Framework for Hyperspectral Imagery Classification

4. Background Purification Framework With Extended Morphological Attribute Profile for Hyperspectral Anomaly Detection

5. Few-Shot Hyperspectral Image Classification With Unknown Classes Using Multitask Deep Learning

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