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LifeCLEF 2021 Teaser: Biodiversity Identification and Prediction Challenges
- 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.
- Subjects :
- 0106 biological sciences
Bird identification
Soundscape
Computer science
Biodiversity
02 engineering and technology
010603 evolutionary biology
01 natural sciences
Plant identification
Machine learning
0202 electrical engineering, electronic engineering, information engineering
Species identification
Species prediction
Sustainable development
business.industry
Environmental resource management
Species distribution model
Field (geography)
Herbarium
AI
Identity (object-oriented programming)
020201 artificial intelligence & image processing
Identification (biology)
business
Snake identification
Subjects
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