UPMC/LIP6 at ImageCLEFannotation 2010

13 years 5 months ago
UPMC/LIP6 at ImageCLEFannotation 2010
In this paper, we present the LIP6 annotation models for the ImageCLEFannotation 2010 task. We study two methods to train and merge the results of different classifiers in order to improve annotation. In particular, we propose a multiview learning model based on a RankingSVM. We also consider the use of the tags matching the visual concept names to improve the scores predicted by the models. The experiments show the difficulty of merging several classifiers and also the interest to have a robust model able to merge relevant information. Our method using tags always improves the results. Key words: SVM, Multi-Class Multi-Label Image Classification, Imbalanced Class Problem, Semi-Supervised Learning, Transductive Learning, Visual Concepts, Ranking SVM
Ali Fakeri-Tabrizi, Sabrina Tollari, Nicolas Usuni
Added 08 Nov 2010
Updated 08 Nov 2010
Type Conference
Year 2010
Where CLEF
Authors Ali Fakeri-Tabrizi, Sabrina Tollari, Nicolas Usunier, Massih-Reza Amini, Patrick Gallinari
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