Automatic Semantic Network Construction for Multi-Layer Annotation of Satellite Images
Résumé
A novel method is presented for annotating satellite images. The labels used for annotation are given by a user with a set of example images. A learning step is then applied to learn the model. The originality of the method is to formulate the problem of semantic annotation to a further extent than a mere probabilistic classification task. The method takes into account the semantical relationships between the concepts by considering a duality between the structure of the model and the structure of the set of labels. The semantical structure of the labels is represented by a semantic network containing three semantical relationships: synonymy, meronymy, and hyponymy. The semantic network is constrained in a hierarchy induced by the links of hyponymy and meronymy. By a procedure of MDL model selection, it is possible to find the optimal semantical structure of the set of labels.
Domaines
Traitement des images [eess.IV]
Origine : Fichiers produits par l'(les) auteur(s)
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