LifeCLEF 2022 teaser: An evaluation of machine-learning based species identification and species distribution prediction
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 in Medically Important scenarios, and (v) FungiCLEF: Fungi recognition from images and metadata.
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | conference_item biblioteca |
| Language: | eng |
| Published: |
Springer
|
| Online Access: | http://agritrop.cirad.fr/605637/ http://agritrop.cirad.fr/605637/1/ID605637.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
dig-cirad-fr-605637 |
|---|---|
| record_format |
koha |
| spelling |
dig-cirad-fr-6056372023-11-29T10:58:40Z http://agritrop.cirad.fr/605637/ http://agritrop.cirad.fr/605637/ LifeCLEF 2022 teaser: 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, Bolon Isabelle, Glotin Hervé, Planqué Robert, Vellinga Willem-Pier, Klinck Holger, Denton Tom, Eggel Ivan, Bonnet Pierre, Müller Henning, Sulc Milan. 2022. In : Advances in information retrieval : 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II. Hagen Matthias (ed.), Verberne Suzan (ed.), Macdonald Craig (ed.), Seifert Christin (ed.), Balog Krisztian (ed.), Norvag Kjetil (ed.), Setty Vinary (ed.). University of Stavanger. Cham : Springer, 390-399. (Lecture Notes in Computer Science, 13186) ISBN 978-3-030-99738-0 European Conference on IR Research (ECIR 2022). 44, Stavanger, Norvège, 10 Avril 2022/14 Avril 2022.https://doi.org/10.1007/978-3-030-99739-7_49 <https://doi.org/10.1007/978-3-030-99739-7_49> LifeCLEF 2022 teaser: 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 Bolon, Isabelle Glotin, Hervé Planqué, Robert Vellinga, Willem-Pier Klinck, Holger Denton, Tom Eggel, Ivan Bonnet, Pierre Müller, Henning Sulc, Milan eng 2022 Springer Advances in information retrieval : 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II 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 in Medically Important scenarios, and (v) FungiCLEF: Fungi recognition from images and metadata. conference_item info:eu-repo/semantics/conferenceObject Conference info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/605637/1/ID605637.pdf text cc_by info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ https://doi.org/10.1007/978-3-030-99739-7_49 10.1007/978-3-030-99739-7_49 https://catalogue-bibliotheques.cirad.fr/cgi-bin/koha/opac-detail.pl?biblionumber=222337 info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-030-99739-7_49 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1007/978-3-030-99739-7_49 info:eu-repo/grantAgreement/EC/H2020/863463//(EU) Co-designed Citizen Observatories Services for the EOS-Cloud/COS4CLOUD |
| institution |
CIRAD FR |
| collection |
DSpace |
| country |
Francia |
| countrycode |
FR |
| component |
Bibliográfico |
| access |
En linea |
| databasecode |
dig-cirad-fr |
| tag |
biblioteca |
| region |
Europa del Oeste |
| libraryname |
Biblioteca del CIRAD Francia |
| language |
eng |
| description |
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 in Medically Important scenarios, and (v) FungiCLEF: Fungi recognition from images and metadata. |
| format |
conference_item |
| author |
Joly, Alexis Goeau, Hervé Kahl, Stefan Picek, Lukáš Lorieul, Titouan Cole, Elijah Deneu, Benjamin Servajean, Maximilien Durso, Andrew Bolon, Isabelle Glotin, Hervé Planqué, Robert Vellinga, Willem-Pier Klinck, Holger Denton, Tom Eggel, Ivan Bonnet, Pierre Müller, Henning Sulc, Milan |
| spellingShingle |
Joly, Alexis Goeau, Hervé Kahl, Stefan Picek, Lukáš Lorieul, Titouan Cole, Elijah Deneu, Benjamin Servajean, Maximilien Durso, Andrew Bolon, Isabelle Glotin, Hervé Planqué, Robert Vellinga, Willem-Pier Klinck, Holger Denton, Tom Eggel, Ivan Bonnet, Pierre Müller, Henning Sulc, Milan LifeCLEF 2022 teaser: An evaluation of machine-learning based species identification and species distribution prediction |
| author_facet |
Joly, Alexis Goeau, Hervé Kahl, Stefan Picek, Lukáš Lorieul, Titouan Cole, Elijah Deneu, Benjamin Servajean, Maximilien Durso, Andrew Bolon, Isabelle Glotin, Hervé Planqué, Robert Vellinga, Willem-Pier Klinck, Holger Denton, Tom Eggel, Ivan Bonnet, Pierre Müller, Henning Sulc, Milan |
| author_sort |
Joly, Alexis |
| title |
LifeCLEF 2022 teaser: An evaluation of machine-learning based species identification and species distribution prediction |
| title_short |
LifeCLEF 2022 teaser: An evaluation of machine-learning based species identification and species distribution prediction |
| title_full |
LifeCLEF 2022 teaser: An evaluation of machine-learning based species identification and species distribution prediction |
| title_fullStr |
LifeCLEF 2022 teaser: An evaluation of machine-learning based species identification and species distribution prediction |
| title_full_unstemmed |
LifeCLEF 2022 teaser: An evaluation of machine-learning based species identification and species distribution prediction |
| title_sort |
lifeclef 2022 teaser: an evaluation of machine-learning based species identification and species distribution prediction |
| publisher |
Springer |
| url |
http://agritrop.cirad.fr/605637/ http://agritrop.cirad.fr/605637/1/ID605637.pdf |
| work_keys_str_mv |
AT jolyalexis lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction AT goeauherve lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction AT kahlstefan lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction AT piceklukas lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction AT lorieultitouan lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction AT coleelijah lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction AT deneubenjamin lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction AT servajeanmaximilien lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction AT dursoandrew lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction AT bolonisabelle lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction AT glotinherve lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction AT planquerobert lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction AT vellingawillempier lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction AT klinckholger lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction AT dentontom lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction AT eggelivan lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction AT bonnetpierre lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction AT mullerhenning lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction AT sulcmilan lifeclef2022teaseranevaluationofmachinelearningbasedspeciesidentificationandspeciesdistributionprediction |
| _version_ |
1787232597023129600 |