A Novel Hyperspectral Unmixing Method with K-Means and VAE Based Network Structure-Reference-Cited by-同舟云学术

A Novel Hyperspectral Unmixing Method with K-Means and VAE Based Network Structure

Published:2022-10-21 Issue: Volume: Page:
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Container-title:Proceedings of the 2022 6th International Conference on Electronic Information Technology and Computer Engineering
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Author:

Xia Zhipeng¹^ORCID,Chen Meng¹^ORCID

Affiliation:

1. Shenyang Institute of Computing Technology, University of Chinese Academy of Sciences, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3573428.3573429

Reference11 articles.

1. Spectral-Spatial Hyperspectral Unmixing Using Nonnegative Matrix Factorization;Guorong Shaoquan;IEEE Transactions on Geoscience and Remote Sensing,2022

2. Xuanwen Tao , Fast Orthogonal Projection for Hyperspectral Unmixing , IEEE Transactions on Geoscience and Remote Sensing Vo . 60 , 2020 . Xuanwen Tao, Fast Orthogonal Projection for Hyperspectral Unmixing, IEEE Transactions on Geoscience and Remote Sensing Vo.60, 2020.

3. Zhang, Xiangrong; Sun, Yujia; Zhang, Jingyan; Wu, Peng; Jiao, Licheng , Hyperspectral Unmixing via Deep Convolutional Neural Networks . IEEE Geoscience and Remote Sensing Letters , (), 1–5, 2018 . Zhang, Xiangrong; Sun, Yujia; Zhang, Jingyan; Wu, Peng; Jiao, Licheng, Hyperspectral Unmixing via Deep Convolutional Neural Networks. IEEE Geoscience and Remote Sensing Letters, (), 1–5, 2018.

4. On the use of small training sets for neural network-based characterization of mixed pixels in remotely sensed hyperspectral images

5. Pixel Unmixing in Hyperspectral Data by Means of Neural Networks

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