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Exquisitor: Breaking the Interaction Barrier for Exploration of 100 Million Images
Abstract : In this demonstration, we present Exquisitor, a media explorer capable of learning user preferences in real-time during interactions with the 99.2 million images of YFCC100M. Exquisitor owes its efficiency to innovations in data representation, compression, and indexing. Exquisitor can complete each interaction round, including learning preferences and presenting the most relevant results, in less than 30 ms using only a single CPU core and modest RAM. In short, Exquisitor can bring large-scale interactive learning to standard desktops and laptops, and even high-end mobile devices.
Cited literature [18 references]
https://hal.inria.fr/hal-02378272
Contributor : Laurent Amsaleg <>
Submitted on : Thursday, January 23, 2020 - 4:50:46 PM
Last modification on : Monday, November 16, 2020 - 9:34:06 AM
Long-term archiving on: : Friday, April 24, 2020 - 3:47:12 PM
Contributor : Laurent Amsaleg <>
Submitted on : Thursday, January 23, 2020 - 4:50:46 PM
Last modification on : Monday, November 16, 2020 - 9:34:06 AM
Long-term archiving on: : Friday, April 24, 2020 - 3:47:12 PM
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exquiz.pdf
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