Interactive Learning for Multimedia at Large
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F20%3A00344396" target="_blank" >RIV/68407700:21730/20:00344396 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-030-45439-5_33" target="_blank" >https://doi.org/10.1007/978-3-030-45439-5_33</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-45439-5_33" target="_blank" >10.1007/978-3-030-45439-5_33</a>
Alternative languages
Result language
angličtina
Original language name
Interactive Learning for Multimedia at Large
Original language description
Interactive learning has been suggested as a key method for addressing analytic multimedia tasks arising in several domains. Until recently, however, methods to maintain interactive performance at the scale of today’s media collections have not been addressed. We propose an interactive learning approach that builds on and extends the state of the art in user relevance feedback systems and high-dimensional indexing for multimedia. We report on a detailed experimental study using the ImageNet and YFCC100M collections, containing 14 million and 100 million images respectively. The proposed approach outperforms the relevant state-of-the-art approaches in terms of interactive performance, while improving suggestion relevance in some cases. In particular, even on YFCC100M, our approach requires less than 0.3 s per interaction round to generate suggestions, using a single computing core and less than 7 GB of main memory.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF15_003%2F0000470" target="_blank" >EF15_003/0000470: Robotics 4 Industry 4.0</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Information Retrieval
ISBN
978-3-030-45438-8
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
16
Pages from-to
495-510
Publisher name
Springer
Place of publication
Cham
Event location
Lisboa
Event date
Apr 14, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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