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LifeCLEF 2021 Teaser: Biodiversity Identification and Prediction Challenges

Authors :
Henning Müller
Ivan Eggel
Hervé Glotin
Hervé Goëau
Elijah Cole
Benjamin Deneu
Stefan Kahl
WP Willem Pier Vellinga
Alexis Joly
Titouan Lorieul
Andrew M. Durso
Maximilien Servajean
Lukás Picek
Rafael Luis Ruiz De Castaneda
Pierre Bonnet
Source :
ECIR 2021: Advances in Information Retrieval, Lecture Notes in Computer Science ISBN: 9783030722395, ECIR (2), Lecture Notes in Computer Science, Lecture Notes in Computer Science-Advances in Information Retrieval
Publication Year :
2021
Publisher :
Springer Nature, 2021.

Abstract

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.

Details

Language :
English
ISBN :
978-3-030-72239-5
978-3-030-72240-1
ISSN :
03029743 and 16113349
ISBNs :
9783030722395 and 9783030722401
Database :
OpenAIRE
Journal :
ECIR 2021: Advances in Information Retrieval, Lecture Notes in Computer Science ISBN: 9783030722395, ECIR (2), Lecture Notes in Computer Science, Lecture Notes in Computer Science-Advances in Information Retrieval
Accession number :
edsair.doi.dedup.....18679c6e64e1c3cdee0fbac2ece15214