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Unsupervised Feature-Learning for Hyperspectral Data with Autoencoders

November 9, 2019

Unsupervised Feature-Learning for Hyperspectral Data with Auto-encoders
Lloyd Windrim, Rishi Ramakrishnan, Arman Melkumyan, Richard J. Murphy and Anna Chlingaryan

Remote Sensing
doi: 10.3390/rs11070864
Year: 2019 , Volume: 11 , Issue: 7
Page: 864

documentation page

the source code on github repo

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1	.pdf	4.44 MB	remotesensing-11-00864

Deep Encoder–Decoder Networks for Classification of Hyperspectral and LiDAR Data
Cross-Attention in Coupled Unmixing Nets for Unsupervised Hyperspectral Super-Resolution
Spectral Superresolution of Multispectral Imagery With Joint Sparse and Low-Rank Learning
Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep (Overview and Toolbox)
CoSpace: Common Subspace Learning from Hyperspectral-Multispectral Correspondences
Learnable Manifold Alignment (LeMA) : A Semi-supervised Cross-modality Learning Framework for Land Cover and Land Use Classification

Unsupervised Feature-Learning for Hyperspectral Data with Autoencoders

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