UPMC-LIP6 at TrecVid'08: Balanced and Unbalanced Forests of Fuzzy Decision Trees for High-Level Feature Detection - Archive ouverte HAL
Communication Dans Un Congrès Année : 2008

UPMC-LIP6 at TrecVid'08: Balanced and Unbalanced Forests of Fuzzy Decision Trees for High-Level Feature Detection

Christophe Marsala
Machine Learning and Information Retrieval
CV
Marcin Detyniecki
Machine Learning and Information Retrieval

Résumé

In this paper, we present the methodology we applied in our submission to the NIST TRECVID’2008 evaluation. We participated in the High-level Feature Extraction task. Our approach is based on the use of a Forest of Fuzzy Decision Trees constructed by means of either a balanced sampling of the development data, or an unbalanced sampling of the development data.

Domaines

Informatique [cs]

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https://hal.science/hal-01305038

Soumis le : mercredi 20 avril 2016-15:58:50

Dernière modification le : mercredi 24 mai 2023-12:27:16

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Dates et versions

hal-01305038 , version 1 (20-04-2016)

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  • HAL Id : hal-01305038 , version 1

Citer

Christophe Marsala, Marcin Detyniecki. UPMC-LIP6 at TrecVid'08: Balanced and Unbalanced Forests of Fuzzy Decision Trees for High-Level Feature Detection. TRECVID 2008 workshop participants notebook papers, Nov 2008, Gaithersburg, MD, United States. ⟨hal-01305038⟩

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