Overview of LifeCLEF 2022: 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, Glotin Hervé, Planqué Robert, Vellinga Willem-Pier, Navine Amanda, Klinck Holger, Denton Tom, Eggel Ivan, Bonnet Pierre, Sulc Milan, Hrúz Marek. 2022. Overview of LifeCLEF 2022: An evaluation of machine-learning based species identification and species distribution prediction. In : Experimental IR meets multilinguality, multimodality, and interaction : 13th International Conference of the CLEF Association, CLEF 2022, Bologna, Italy, September 5–8, 2022, Proceedings. Barron-Cedeno Alberto (ed.), Da San Martino Giovanni (ed.), Faggioli Guglielmo (ed.), Ferro Nicola (ed.), Degli Esposti Mirko (ed.), Sebastiani Fabrizio (ed.), Macdonald Craig (ed.), Pasi Gabriella (ed.), Hanbury Allan (ed.), Potthast Martin (ed.). University of Bologna. Cham : Springer, 257-285. (Lecture Notes in Computer Science, 13390) ISBN 978-3-031-13642-9 International Conference of the CLEF Association (CLEF 2022). 13, Bologne, Italie, 5 Septembre 2022/8 Septembre 2022.

https://doi.org/10.1007/978-3-031-13643-6_19

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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 on a global scale, and (v) FungiCLEF: fungi recognition as an open set classification problem. This paper overviews the motivation, methodology and main outcomes of that five challenges.

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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