Hyperspectral Target Detection-Based 2-D–3-D Parallel Convolutional Neural Networks for Hyperspectral Image Classification-Reference-Cited by-同舟云学术

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Hyperspectral Target Detection-Based 2-D–3-D Parallel Convolutional Neural Networks for Hyperspectral Image Classification

Published:2024 Issue: Volume:17 Page:9451-9469
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Chen Shih-Yu¹^ORCID,Hsu Kai-Hsun¹,Kuo Tzu-Hsien¹

Affiliation:

1. Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, Yunlin, Taiwan

Funder

Intelligent Recognition Industry Service Center

Featured Areas Research Center

Ministry of Education in Taiwan

National Science and Technology Council

Isuzu Optics Corporation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/4609443/10330207/10509762.pdf?arnumber=10509762

Reference56 articles.

1. Precision agriculture using hyperspectral remote sensing and GIS

2. Real-time defect and freshness inspection on chicken eggs using hyperspectral imaging

3. Detection of Insect Damage in Green Coffee Beans Using VIS-NIR Hyperspectral Imaging

4. Applications of hyperspectral remote sensing and GIS for assessing forest health and air pollution

5. Almond defect and freshness inspection system using hyperspectral imaging and deep learning techniques

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