Deneu Benjamin, Servajean Maximilien, Bonnet Pierre, Munoz François, Joly Alexis.
2020. Participation of LIRMM / Inria to the GeoLifeCLEF 2020 challenge.
In : Working Notes of CLEF 2020 - Conference and Labs of the Evaluation Forum. Cappellato Linda (ed.), Eickhoff Carsten (ed.), Ferro Nicola (ed.), Névéol Aurélie (ed.)
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Version publiée
- Anglais
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Note générale : Le congrès s'est tenu en ligne
Résumé : This paper describes the methods that we have implemented in the context of the GeoLifeCLEF 2020 machine learning challenge. The goal of this challenge is to advance the state-of-the-art in location- based species recommendation on a very large dataset of 1.9 million species observations, paired with high-resolution remote sensing imagery, land cover data, and altitude. We provide a detailed description of the algorithms and methodology, developed by the LIRMM / Inria team, in order to facilitate the understanding and reproducibility of the obtained results.
Mots-clés libres : Species distribution models, Evaluation, Model performance, Environmental data, Biodiversity
Auteurs et affiliations
- Deneu Benjamin, CIRAD-BIOS-UMR AMAP (FRA)
- Servajean Maximilien, CNRS (FRA)
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Bonnet Pierre, CIRAD-BIOS-UMR AMAP (FRA)
ORCID: 0000-0002-2828-4389
- Munoz François, Université Grenoble Alpes (FRA)
- Joly Alexis, INRIA (FRA)
Source : Cirad-Agritrop (https://agritrop.cirad.fr/598369/)
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