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A Simulated User Study of Image Browsing Using High-Level Classification

Identifieur interne : 001436 ( Main/Exploration ); précédent : 001435; suivant : 001437

A Simulated User Study of Image Browsing Using High-Level Classification

Auteurs : Teerapong Leelanupab [Royaume-Uni] ; Yue Feng [Royaume-Uni] ; Vassilios Stathopoulos [Royaume-Uni] ; Joemon M. Jose [Royaume-Uni]

Source :

RBID : ISTEX:20D632A2B006B1513322E59A2E465E2F2BB2FE71

Abstract

Abstract: In this paper, we present a study of adaptive image browsing, based on high-level classification. The underlying hypothesis is that the performance of a browsing model can be improved by integrating high-level semantic concepts. We introduce a multi-label classification model designed to alleviate a binary classification problem in image classification. The effectiveness of this approach is evaluated by using a simulated user evaluation methodology. The results show that the classification assists users to narrow down the search domain and to retrieve more relevant results with respect to less amount of browsing effort.

Url:
DOI: 10.1007/978-3-642-10543-2_3


Affiliations:


Links toward previous steps (curation, corpus...)


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