Remote Sensing Image Fusion Using Hierarchical Multimodal Probabilistic Latent Semantic Analysis

The generative semantic nature of probabilistic topic models has recently shown encouraging results within the remote sensing image fusion field when conducting land cover categorization. However, standard topic models have not yet been adapted to the inherent complexity of remotely sensed data, whi...

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Vydané v:	IEEE journal of selected topics in applied earth observations and remote sensing Ročník 11; číslo 12; s. 4982 - 4993
Hlavní autori:	Fernandez-Beltran, Ruben, Haut, Juan M., Paoletti, Mercedes E., Plaza, Javier, Plaza, Antonio, Pla, Filiberto
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.12.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Adaptation models Classification Clustering Computer vision Data Data integration Data models Defense industry Frameworks Image fusion Image processing Imaging techniques Land cover Multisensor fusion multispectral imaging (MSI) probabilistic latent semantic analysis (pLSA) Probabilistic logic Radar imaging Remote sensing SAR (radar) Semantic analysis Semantics Synthetic aperture radar synthetic aperture radar (SAR)
ISSN:	1939-1404, 2151-1535
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