Quantification: extracting quantitative information from correlated multimodal dataset - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2020

Quantification: extracting quantitative information from correlated multimodal dataset

Résumé

In this lecture, we will focus on the extraction of quantitative information from correlated multimodal datasets. We will review the different categories of questions relying on the quantification of correlated multimodal datasets, from the validation of a new imaging modality to the integration of heterogeneous information, based on examples. A particular focus will be done on the confidence estimation on these quantification, and the different possibilities to quantify this confidence in the correlation, in the medical and biological fields. OUTLINE Why do you want to fuse multimodal information? Once is fused, how do you exploit the spatial correlation? How do you check it is correctly fused?
2020_COMULISVIB_Quantification.pdf (3.68 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Licence : CC BY NC - Paternité - Pas d'utilisation commerciale

Dates et versions

hal-04214173 , version 1 (25-09-2023)

Identifiants

  • HAL Id : hal-04214173 , version 1

Citer

Perrine Paul-Gilloteaux. Quantification: extracting quantitative information from correlated multimodal dataset. IMAGE PROCESSING FOR CORRELATED AND MULTIMODAL IMAGING TECHNIQUES, VIB Training, Oct 2020, Ghent, Belgium. ⟨hal-04214173⟩
6 Consultations
1 Téléchargements

Partager

Gmail Facebook X LinkedIn More