Notice bibliographique
- Notice
Type(s) de contenu et mode(s) de consultation : Texte noté : électronique
Auteur(s) : Ionescu, Radu Tudor
Popescu, Marius
Titre(s) : Knowledge transfer between computer vision and text mining [Texte électronique] : similarity-based learning approaches / Radu Tudor Ionescu, Marius Popescu
Publication : [Cham] : Springer international publishing AG, copyright 2016
Description matérielle : 1 ressource dématérialisée
Collection : Advances in computer vision and pattern recognition, ISSN 2191-6594
Lien à la collection : Advances in computer vision and pattern recognition (Internet)
Comprend : Motivation and Overview ; Learning Based on Similarity ; Part I: Knowledge Transfer
from Text Mining to Computer Vision ; State of the Art Approaches for Image Classification
; Local Displacement Estimation of Image Patches and Textons ; Object Recognition
with the Bag of Visual Words Model ; Part II: Knowledge Transfer from Computer Vision
to Text Mining ; State of the Art Approaches for String and Text Analysis ; Local
Rank Distance ; Native Language Identification with String Kernels ; Spatial Information
in Text Categorization ; Conclusions.
Note(s) : Notes bibliogr.
This ground-breaking text/reference diverges from the traditional view that computer
vision (for image analysis) and string processing (for text mining) are separate and
unrelated fields of study, propounding that images and text can be treated in a similar
manner for the purposes of information retrieval, extraction and classification. Highlighting
the benefits of knowledge transfer between the two disciplines, the text presents
a range of novel similarity-based learning techniques founded on this approach. Topics
and features: Describes a variety of similarity-based learning approaches, including
nearest neighbor models, local learning, kernel methods, and clustering algorithms
Presents a nearest neighbor model based on a novel dissimilarity for images, and applies
this for handwritten digit recognition and texture analysis Discusses a novel kernel
for (visual) word histograms, as well as several kernels based on pyramid representation,
and uses these for facial expression recognition and text categorization by topic
Introduces an approach based on string kernels for native language identification
Contains links for downloading relevant open source code With a foreword by Prof.
Florentina Hristea This unique work will be of great benefit to researchers, postgraduate
and advanced undergraduate students involved in machine learning, data science, text
mining and computer vision. Dr. Radu Tudor Ionescu is an Assistant Professor in the
Department of Computer Science at the University of Bucharest, Romania. Dr. Marius
Popescu is an Associate Professor at the same institution
Sujet(s) : Apprentissage automatique
Exploration de données
Vision par ordinateur
Indice(s) Dewey :
006.03 (23e éd.) = Méthodes informatiques particulières - Dictionnaires et encyclopédies
Identifiants, prix et caractéristiques : ISBN 9783319303673. - ISBN 3319303678. - ISBN 9783319303659 (erroné). - ISBN 3319303651
(erroné)
Identifiant de la notice : ark:/12148/cb45345590w
Notice n° :
FRBNF45345590
(notice reprise d'un réservoir extérieur)
