loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: P. Zuccarello 1 ; E. de Ves 1 ; T. Leon 2 ; G. Ayala 2 and J. Domingo 3

Affiliations: 1 University de Valencia, Spain ; 2 University of Valencia, Spain ; 3 Institut of Robotics, University of Valencia, Spain

Keyword(s): Visual information retrieval,relevance feedback,logistic regresion.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: This paper presents a new algorithm for content based retrieval systems in large databases. The objective of these systems is to find the images which are as similar as possible to a user query from those contained in the global image database without using textual annotations attached to the images. The procedure proposed here to address this problem is based on logistic regression model: the algorithm considers the probability of an image to belong to the set of those desired by the user. In this work a relevance proabaility π(I) is a quantity wich reflects the estimate of the relevance of the image I with respect to the user’s preferences. The problem of the small sample size with respect to the number of features is solved by adjusting several partial linear models and combining its relevance probabilitis by means of an ordered averaged weighted operator. Experimental results are shown to evaluate the method on a large image database in term of the average number of iterations ne eded to find a target image. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.14.251.103

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Zuccarello, P.; de Ves, E.; Leon, T.; Ayala, G. and Domingo, J. (2007). A NOVEL RELEVANCE FEEDBACK PROCEDURE BASED ON LOGISTIC REGRESSION AND OWA OPERATOR FOR CONTENT-BASED IMAGE RETRIEVAL SYSTEM. In Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISIGRAPP 2007) - Volume 2: VISAPP; ISBN 978-972-8865-74-0; ISSN 2184-4321, SciTePress, pages 167-172. DOI: 10.5220/0002059701670172

@conference{visapp07,
author={P. Zuccarello. and E. {de Ves}. and T. Leon. and G. Ayala. and J. Domingo.},
title={A NOVEL RELEVANCE FEEDBACK PROCEDURE BASED ON LOGISTIC REGRESSION AND OWA OPERATOR FOR CONTENT-BASED IMAGE RETRIEVAL SYSTEM},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISIGRAPP 2007) - Volume 2: VISAPP},
year={2007},
pages={167-172},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002059701670172},
isbn={978-972-8865-74-0},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISIGRAPP 2007) - Volume 2: VISAPP
TI - A NOVEL RELEVANCE FEEDBACK PROCEDURE BASED ON LOGISTIC REGRESSION AND OWA OPERATOR FOR CONTENT-BASED IMAGE RETRIEVAL SYSTEM
SN - 978-972-8865-74-0
IS - 2184-4321
AU - Zuccarello, P.
AU - de Ves, E.
AU - Leon, T.
AU - Ayala, G.
AU - Domingo, J.
PY - 2007
SP - 167
EP - 172
DO - 10.5220/0002059701670172
PB - SciTePress