Hyperspectral Unmixing for Additive Nonlinear Models With a 3-D-CNN Autoencoder Network-Reference-Cited by-同舟云学术

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Hyperspectral Unmixing for Additive Nonlinear Models With a 3-D-CNN Autoencoder Network

Published:2022 Issue: Volume:60 Page:1-15
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Zhao Min,Wang Mou^ORCID,Chen Jie^ORCID,Rahardja Susanto^ORCID

Funder

National Key Research and Development Program of China

Higher Education Discipline Innovation Project

Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09503107.pdf?arnumber=9503107

Cited by 45 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Unsupervised Nonlinear Hyperspectral Unmixing Based on an Extended Multilinear Mixing Model-Inspired Dual-Stream Network;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

2. A multiscale enhanced pavement crack segmentation network coupling spectral and spatial information of UAV hyperspectral imagery;International Journal of Applied Earth Observation and Geoinformation;2024-04

3. Hyperspectral Unmixing With Multi-Scale Convolution Attention Network;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

4. Image Processing and Machine Learning for Hyperspectral Unmixing: An Overview and the HySUPP Python Package;IEEE Transactions on Geoscience and Remote Sensing;2024

5. A Supervised Approach for Estimating Fractional Abundances of Binary Intimate Mixtures;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

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