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Prediction of photo shareability using supervisedlearning
KTH, School of Computer Science and Communication (CSC).
2013 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Many photos are taken every day. Some of them are shared to friends, acquaintances or family. Automatic prediction of what photos are shareable is investigated. The prediction techniques use supervised machine learning, trying to separate shareable images from non-shareable images. High performing prediction is shown to be hard to solve accurately using the chosen approach.

Abstract [sv]

Varje dag tas många fotografier. Några av dessa foton delas till vänner, bekanta eller familj. Automatisk förutsägelse av vilka fotografier som är delbara undersöks. Förutsägelseteknikerna försöker med hjälp av maskininlärning separera de delbara fotografierna från de som ej är delbara. Högpresterande förutsägning visas vara svårt att lösa med det valda tillvägagångssättet.

Place, publisher, year, edition, pages
National Category
Computer Science
URN: urn:nbn:se:kth:diva-142431OAI: diva2:700508
Educational program
Master of Science in Engineering - Computer Science and Technology
Available from: 2014-03-11 Created: 2014-03-04 Last updated: 2014-03-11Bibliographically approved

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School of Computer Science and Communication (CSC)
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