Annotating images with suggestions - user study of a tagging system

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F12%3APU101780" target="_blank" >RIV/00216305:26230/12:PU101780 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-642-33140-4_14" target="_blank" >http://dx.doi.org/10.1007/978-3-642-33140-4_14</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-33140-4_14" target="_blank" >10.1007/978-3-642-33140-4_14</a>

Result language
angličtina
Original language name
Annotating images with suggestions - user study of a tagging system
Original language description
This paper explores the concept of image-wise tagging. It introduces a web-based user interface for image annotation, and a novel method for modeling dependencies of tags using Restricted Boltzmann Machines which is able to suggest probable tags for an image based on previously assigned tags. According to our user study, our tag suggestion methods improve both user experience and annotation speed. Our results demonstrate that large datasets with semantic labels (such as in TRECVID Semantic Indexing) canbe annotated much more efficiently with the proposed approach than with current class-domain-wise methods, and produce higher quality data.
Czech name
—
Czech description
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Project
<a href="/en/project/7E12055" target="_blank" >7E12055: GLOCAL: Event-based Retrieval of Networked Media</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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