Výsledky vyhledávání - "Lefort, Riwal"

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Bi-class classification of humpback whale sound units against complex background noise with Deep Convolution Neural Network

Autor: Dorian, Cazau, Lefort, Riwal, Bonnel, Julien, Zarader, Jean-Luc, Adam, Olivier

Automatically detecting sound units of humpback whales in complex time-varying background noises is a current challenge for scientists. In this paper, we explore the applicability of Convolution Neural Network (CNN) method for this task. In the evalu

Externí odkaz: http://arxiv.org/abs/1703.10887

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Akademický článek

Direct regressions for underwater acoustic source localization in fluctuating oceans

Autor: Lefort, Riwal, Real, Gaultier, Drémeau, Angélique

Publikováno v: In Applied Acoustics 15 January 2017 116:303-310

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Distant Event Prediction Based on Sequential Rules

Autor: Fahed, Lina, Lenca, Philippe, Haralambous, Yannis, Lefort, Riwal

Publikováno v: Data Science and Pattern Recognition
Data Science and Pattern Recognition, 2020, 4 (1), pp.1-23

International audience; Event prediction in sequence databases is an important and challenging data mining task. We focus on the specific case of prediction of distant events. Our aim is to mine sequential association rules with consequents that are

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::a55fbb7775519163a1341e996dd79dbd
https://hal.science/hal-02562021

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Prédiction d'évènements distants basée sur les règles séquentielles

Autor: Fahed, Lina, Lenca, Philippe, Haralambous, Yannis, Lefort, Riwal, Tallec, Marie-Laure

Publikováno v: Actes EGC 2019 : Extraction et gestion des connaissances
EGC 2019 : Extraction et gestion des connaissances
EGC 2019 : Extraction et gestion des connaissances, Jan 2019, Metz, France. pp.309-314

International audience; Events prediction in sequences database is a challenging task that can be approached with data mining. In this paper, we focus on the specific goal of the prediction of distant events by mining sequential rules and propose the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______2592::10d5427363ba1826dfb1cf495ac57fdf
https://hal.archives-ouvertes.fr/hal-01962067/file/egc19_shortVersion.pdf

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