Semi-supervised learning of heterogeneous data in remote sensing imagery

Author:

Benedetto J.,Czaja W.,Dobrosotskaya J.,Doster T.,Duke K.,Gillis D.

Publisher

SPIE

Cited by 14 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. Spatial Spectral Schroedinger Eigenmaps Approach Based on Spectral Angle Distance for Hyperspectral Imagery Classification;Journal of the Indian Society of Remote Sensing;2021-08-17

2. Transport Model for Feature Extraction;SIAM Journal on Mathematics of Data Science;2021-01

3. Sumi-supervised deep autoencoder network for graph-based dimensionality reduction in hyperspectral imagery;Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV;2018-05-08

4. Scattering transforms and classification of hyperspectral images;Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV;2018-05-08

5. Semi-supervised normalized embeddings for land-use classification from multiple view data;Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV;2018-05-08

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