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Semantic Annotation of Satellite Images using Latent Dirichlet Allocation

M. Lienou 1 M. Datcu 1 H. Maître 1
1 LTCI - Laboratoire Traitement et Communication de l'Information
Abstract : We a use a semantic learning model to affect user oriented names to satellite image regions. After a supervised classification method of training subsets, we proceed to an automatic labeling by use of a Latent Dirichlet Allocation method (LDA) which does not take into consideration the adjacency relationship between visual words.
keyword : Semantic Annotation LDA
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Submitted on : Saturday, January 15, 2011 - 4:22:01 PM
Last modification on : Friday, July 31, 2020 - 10:44:07 AM

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  • HAL Id : hal-00556162, version 1

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CNRS | INSTITUT-TELECOM | PARISTECH | LTCI

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M. Lienou, M. Datcu, H. Maître. Semantic Annotation of Satellite Images using Latent Dirichlet Allocation. IEEE Geoscience and Remote Sensing Letters, IEEE - Institute of Electrical and Electronics Engineers, 2010, 7 (1), pp.28-32. ⟨hal-00556162⟩

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