LifeCLEF 2022 teaser: An evaluation of machine-learning based species identification and species distribution prediction

Joly Alexis, Goeau Hervé, Kahl Stefan, Picek Lukáš, Lorieul Titouan, Cole Elijah, Deneu Benjamin, Servajean Maximilien, Durso Andrew, Bolon Isabelle, Glotin Hervé, Planqué Robert, Vellinga Willem-Pier, Klinck Holger, Denton Tom, Eggel Ivan, Bonnet Pierre, Müller Henning, Sulc Milan. 2022. LifeCLEF 2022 teaser: An evaluation of machine-learning based species identification and species distribution prediction. In : Advances in information retrieval : 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II. Hagen Matthias (ed.), Verberne Suzan (ed.), Macdonald Craig (ed.), Seifert Christin (ed.), Balog Krisztian (ed.), Norvag Kjetil (ed.), Setty Vinary (ed.). University of Stavanger. Cham : Springer, 390-399. (Lecture Notes in Computer Science, 13186) ISBN 978-3-030-99738-0 European Conference on IR Research (ECIR 2022). 44, Stavanger, Norvège, 10 Avril 2022/14 Avril 2022.

https://doi.org/10.1007/978-3-030-99739-7_49

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Résumé : Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying plants, animals and fungi is hindering the aggregation of new data and knowledge. Identifying and naming living organisms is almost impossible for the general public and is often difficult even for professionals and naturalists. Bridging this gap is a key step towards enabling effective biodiversity monitoring systems. The LifeCLEF campaign, presented in this paper, has been promoting and evaluating advances in this domain since 2011. The 2022 edition proposes five data-oriented challenges related to the identification and prediction of biodiversity: (i) PlantCLEF: very large-scale plant identification, (ii) BirdCLEF: bird species recognition in audio soundscapes, (iii) GeoLifeCLEF: remote sensing based prediction of species, (iv) SnakeCLEF: Snake Species Identification in Medically Important scenarios, and (v) FungiCLEF: Fungi recognition from images and metadata.

Agences de financement européennes : European Commission

Programme de financement européen : H2020

Projets sur financement : (EU) Co-designed Citizen Observatories Services for the EOS-Cloud

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