Accéder directement au contenu Accéder directement à la navigation
Article dans une revue

Human expert fusion for image classification

Abstract : In image classification, merging the opinion of several human experts is very important for different tasks such as the evaluation or the training. Indeed, the ground truth is rarely known before the scene imaging. We propose here different models in order to fuse the informations given by two or more experts. The considered unit for the classification, a small tile of the image, can contain one or more kind of the considered classes given by the experts. A second problem that we have to take into account, is the amount of certainty of the expert has for each pixel of the tile. In order to solve these problems we define five models in the context of the Dempster-Shafer Theory and in the context of the Dezert-Smarandache Theory and we study the possible decisions with these models.
Liste complète des métadonnées

Littérature citée [7 références]  Voir  Masquer  Télécharger

https://hal.archives-ouvertes.fr/hal-00286589
Contributeur : Arnaud Martin <>
Soumis le : mercredi 11 juin 2008 - 03:19:01
Dernière modification le : vendredi 13 décembre 2019 - 10:42:05
Archivage à long terme le : : vendredi 28 mai 2010 - 18:59:20

Fichiers

MartinISJ2006.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-00286589, version 1
  • ARXIV : 0806.1798

Citation

Arnaud Martin, Christophe Osswald. Human expert fusion for image classification. INFORMATION & SECURITY. An International Journal, 2006, 20, pp.122-141. ⟨hal-00286589⟩

Partager

Métriques

Consultations de la notice

312

Téléchargements de fichiers

231