Learning prototype-based classification rules in a boosting framework: application to real-world and medical image categorization

Learning prototype-based classification rules in a boosting framework: application to real-world and medical image categorization

Résumé en français non disponible

Bibliographic Details
Main Author: Piro, Paolo
Language:ENG
Published: Université de Nice Sophia-Antipolis 2010
Subjects:
[INFO:INFO_HC] Computer Science/Human-Computer Interaction
images
indexation
classification
Sparse Multiscale Patches (SMP)
knearest neighbor (k-NN)
Universal Nearest Neighbors (UNN)
MLNN algorithm
medical image classification
radiographic images
Online Access:http://tel.archives-ouvertes.fr/tel-00590403
http://tel.archives-ouvertes.fr/docs/00/59/04/03/PDF/piro_phd_thesis.pdf
id ndltd-CCSD-oai-tel.archives-ouvertes.fr-tel-00590403
record_format oai_dc
spelling ndltd-CCSD-oai-tel.archives-ouvertes.fr-tel-005904032013-01-07T17:42:10Z http://tel.archives-ouvertes.fr/tel-00590403 http://tel.archives-ouvertes.fr/docs/00/59/04/03/PDF/piro_phd_thesis.pdf Learning prototype-based classification rules in a boosting framework: application to real-world and medical image categorization Piro, Paolo [INFO:INFO_HC] Computer Science/Human-Computer Interaction images indexation classification Sparse Multiscale Patches (SMP) knearest neighbor (k-NN) Universal Nearest Neighbors (UNN) MLNN algorithm medical image classification radiographic images Résumé en français non disponible 2010-01-18 ENG PhD thesis Université de Nice Sophia-Antipolis
collection NDLTD
language ENG
sources NDLTD
topic [INFO:INFO_HC] Computer Science/Human-Computer Interaction
images
indexation
classification
Sparse Multiscale Patches (SMP)
knearest neighbor (k-NN)
Universal Nearest Neighbors (UNN)
MLNN algorithm
medical image classification
radiographic images
spellingShingle [INFO:INFO_HC] Computer Science/Human-Computer Interaction
images
indexation
classification
Sparse Multiscale Patches (SMP)
knearest neighbor (k-NN)
Universal Nearest Neighbors (UNN)
MLNN algorithm
medical image classification
radiographic images
Piro, Paolo
Learning prototype-based classification rules in a boosting framework: application to real-world and medical image categorization
description Résumé en français non disponible
author Piro, Paolo
author_facet Piro, Paolo
author_sort Piro, Paolo
title Learning prototype-based classification rules in a boosting framework: application to real-world and medical image categorization
title_short Learning prototype-based classification rules in a boosting framework: application to real-world and medical image categorization
title_full Learning prototype-based classification rules in a boosting framework: application to real-world and medical image categorization
title_fullStr Learning prototype-based classification rules in a boosting framework: application to real-world and medical image categorization
title_full_unstemmed Learning prototype-based classification rules in a boosting framework: application to real-world and medical image categorization
title_sort learning prototype-based classification rules in a boosting framework: application to real-world and medical image categorization
publisher Université de Nice Sophia-Antipolis
publishDate 2010
url http://tel.archives-ouvertes.fr/tel-00590403
http://tel.archives-ouvertes.fr/docs/00/59/04/03/PDF/piro_phd_thesis.pdf
work_keys_str_mv AT piropaolo learningprototypebasedclassificationrulesinaboostingframeworkapplicationtorealworldandmedicalimagecategorization
_version_ 1716396689947885568

Similar Items