High-Level Feature Detection with Forests of Fuzzy Decision Trees combined with the RankBoost - Archive ouverte HAL
Communication Dans Un Congrès Année : 2007

High-Level Feature Detection with Forests of Fuzzy Decision Trees combined with the RankBoost

Christophe Marsala
Machine Learning and Information Retrieval
CV
Marcin Detyniecki
Machine Learning and Information Retrieval
Nicolas Usunier
  • Fonction : Auteur
  • PersonId : 933831
Machine Learning and Information Retrieval
Massih-Reza Amini
Machine Learning and Information Retrieval

Résumé

In this paper, we present the methodology we applied in our submission to the NIST TRECVID’2007 evaluation. We participated in the High-level Feature Extraction task. Our approach is based on the use of a Forest of Fuzzy Decision Trees combined with the RankBoost algorithm.

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Informatique [cs]

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https://hal.science/hal-01336167

Soumis le : mercredi 22 juin 2016-16:37:08

Dernière modification le : jeudi 14 mars 2024-14:40:45

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Dates et versions

hal-01336167 , version 1 (22-06-2016)

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  • HAL Id : hal-01336167 , version 1

Citer

Christophe Marsala, Marcin Detyniecki, Nicolas Usunier, Massih-Reza Amini. High-Level Feature Detection with Forests of Fuzzy Decision Trees combined with the RankBoost. TRECVID 2007 workshop participants notebook papers, Nov 2007, Gaithersburg, MD, United States. ⟨hal-01336167⟩

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