Title:	LifeCLEF 2021 Teaser: Biodiversity Identification and Prediction Challenges
Authors:	Joly, Alexis Goëau, Hervé Cole, Elijah Kahl, Stefan Picek, Lukáš Glotin, Hervé Deneu, Benjamin Servajean, Maximillien Lorieul, Titouan Vellinga, Willem-Pier Bonnet, Pierre Durso, Andrew M. de Castañeda, Rafael Ruiz Eggel, Ivan Müller, Henning
Citation:	JOLY, A. GOËAU, H. COLE, E. KAHL, S. PICEK, L. GLOTIN, H. DENEU, B. SERVAJEAN, M. LORIEUL, T. VELLINGA, W. BONNET, P. DURSO, AM. DE CASTAÑEDA, RR. EGGEL, I. MÜLLER, H. LifeCLEF 2021 Teaser: Biodiversity Identification and Prediction Challenges. In Advances in Information Retrieval 43rd European Conference on IR Research, ECIR 2021, Virtual Event, March 28 – April 1, 2021, Proceedings, Part II. Cham: Springer Nature, 2021. s. 601-607. ISBN: 978-3-030-72239-5 , ISSN: 0302-9743
Issue Date:	2021
Publisher:	Springer Nature
Document type:	konferenční příspěvek ConferenceObject
URI:	2-s2.0-85107353373 http://hdl.handle.net/11025/47276
ISBN:	978-3-030-72239-5
ISSN:	0302-9743
Keywords in different language:	AI;Biodiversity;Bird identification;Machine learning;Plant identification;Snake identification;Species distribution model;Species identification;Species prediction
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 2021 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: image-based snake identification.
Rights:	Plný text je přístupný v rámci univerzity přihlášeným uživatelům. © Springer
Appears in Collections:	Konferenční příspěvky / Conference Papers (KKY) OBD

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.