Title: Overview of LifeCLEF 2020: A System-Oriented Evaluation of Automated Species Identification and Species Distribution Prediction
Authors: Joly, Alexis
Goëau, Hervé
Kahl, Stefan
Deneu, Benjamin
Servajean, Maximillien
Cole, Elijah
Picek, Lukáš
de Castañeda, Rafael Ruiz
Bolon, Isabelle
Durso, Andrew
Lorieul, Titouan
Botella, Christophe
Glotin, Hervé
Champ, Julien
Eggel, Ivan
Vellinga, Willem-Pier
Bonnet, Pierre
Müller, Henning
Citation: JOLY, A. GOËAU, H. KAHL, S. DENEU, B. SERVAJEAN, M. COLE, E. PICEK, L. DE CASTAÑEDA, RR. BOLON, I. DURSO, A. LORIEUL, T. BOTELLA, Ch. GLOTIN, H. CHAMP, J. EGGEL, I. VELLINGA, W. BONNET, P. MÜLLER, H.Overview of LifeCLEF 2020: A System-Oriented Evaluation of Automated Species Identification and Species Distribution Prediction. In: Experimental IR Meets Multilinguality, Multimodality, and Interaction 11th International Conference of the CLEF Association, CLEF 2020, Thessaloniki, Greece, September 22–25, 2020, Proceedings. Cham: Springer, 2020. s. 342-363. ISBN 978-3-030-58218-0, ISSN 0302-9743.
Issue Date: 2020
Publisher: Springer
Document type: konferenční příspěvek
URI: 2-s2.0-85092127389
ISBN: 978-3-030-58218-0
ISSN: 0302-9743
Keywords in different language: biodiversity, machine learning, AI, species identification ,plant identification, bird identification,species distribution mode,snake identification.
Abstract in different language: 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 and animals in the field is hindering the aggregation of new data and knowledge. Identifying and naming living plants or animals 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 2020 edition proposes four data-oriented challenges related to the identification and prediction of biodiversity: (i) PlantCLEF: cross-domain plant identification based on herbarium sheets (ii) BirdCLEF: bird species recognition in audio soundscapes, (iii) GeoLifeCLEF: location-based prediction of species based on environmental and occurrence data, and (iv) SnakeCLEF: snake identification based on image and geographic location.
Rights: © Springer
Appears in Collections:Konferenční příspěvky / Conference papers (NTIS)
Konferenční příspěvky / Conference Papers (KKY)

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Please use this identifier to cite or link to this item: http://hdl.handle.net/11025/42938

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