Evolving Block-Based Convolutional Neural Network for Hyperspectral Image Classification-Reference-Cited by-同舟云学术

Evolving Block-Based Convolutional Neural Network for Hyperspectral Image Classification

Published:2022 Issue: Volume:60 Page:1-21
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Lu Zhenyu¹^ORCID,Liang Shaoyang²,Yang Qiang¹^ORCID,Du Bo³

Affiliation:

1. School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, China

2. School of Electronics and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, China

3. Hubei Key Laboratory of Multimedia and Network Communication Engineering, National Engineering Research Center for Multimedia Software, School of Computer Science, Institute of Artificial Intelligence, Wuhan University, Wuhan, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Natural Science Foundation of the Jiangsu Higher Education Institutions of China

Startup Foundation for Introducing Talent of the Nanjing University of Information Science and Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09737511.pdf?arnumber=9737511

Reference63 articles.

1. Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Neural Networks

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

3. Genetic CNN

4. Automatically Designing CNN Architectures Using the Genetic Algorithm for Image Classification

5. Evolving Deep Convolutional Neural Networks for Image Classification

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