Dual-Branch Autoencoder with Clustering Information for Hyperspectral Blind Unmixing

Deep learning methods, especially autoencoder-based methods, have become increasingly prevalent in the domain of hyperspectral blind unmixing. However, many models still have a limitation, that is, they cannot fully extract spatial and spectral information from hyperspectral images. In this paper, a...

Full description

Bibliographic Details

Published in:	IEEE International Geoscience and Remote Sensing Symposium proceedings pp. 9139 - 9142
Main Authors:	Zong, Hongru, Liu, Jianjun
Format:	Conference Proceeding
Language:	English
Published:	IEEE 07.07.2024
Subjects:	autocoder clustering information Convolution Data mining Deep learning Geoscience and remote sensing hyperspectral blind unmixing Hyperspectral imaging Task analysis
ISSN:	2153-7003
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!