TY  - JOUR
ID  - Joly, A. et al. (2025). LifeCLEF 2025 Teaser: Challenges on Species Presence Prediction and Identification, and Individual Animal Identification. In: Hauff, C., et al. Advances in Information Retrieval. ECIR 2025. Lecture Notes in Computer Science, vol 15
T1  - Challenges on Species Presence Prediction and Identification, and Individual Animal Identification, Springer Lecture Notes in Computer Science, Proceedings of CLEF 2025, Madrid, Spain, 2025.
A1  - Joly, Alexis
A1  - Picek, Lukas
A1  - Botella, Christophe
A1  - Marcos, Diego
A1  - Leblanc, Cesar
A1  - Larcher, Théo
A1  - Kahl, Stefan
A1  - Goëau, Hervé
A1  - Bonnet, Pierre
A1  - Klinck, Holger
A1  - maximilien Servajean
A1  - Matas, Jiří
A1  - Planqué, Robert
A1  - Vellinga, Willem-Pier
A1  - denton, Tom
A1  - Müller, Henning
JA  - Lecture Notes in Computer Science, vol 15576. Springer, Cham
Y1  - 2025
VL  - 15576
SP  - 373
EP  - 381
SN  - 978-3-031-88719-2
UR  - https://link.springer.com/chapter/10.1007/978-3-031-88720-8_57#citeas
M2  - doi: https://doi.org/10.1007/978-3-031-88720-8_57
KW  - Biodiversity Machine Learning AI Species Individual Identification Prediction Species Distribution Modeling
N2  - Accurate identification, monitoring, and understanding of species distribution is important for biodiversity conservation, invasive species control, understanding climate change, and ecosystem management. Current methodologies for species identification, animal re-identification, and large-scale population monitoring are both resource-intensive and technically complex, posing significant challenges for widespread implementation. This highlights a need for automated, scalable solutions to enhance efficiency and accuracy. Since 2011, the LifeCLEF lab has driven progress in this field by organizing annual challenges to promote innovation in biodiversity informatics. The 2025 edition introduces five  –  one new, and four continued – data-driven tasks aimed at addressing current challenges in species recognition: (i) AnimalCLEF: multi-species individual animal identification, (ii) BirdCLEF: bird species identification in soundscape recordings, (iii) FungiCLEF: few shot classification with rare fungi species, (iv) GeoLifeCLEF: multi-modal species prediction using remote sensing and large-scale biodiversity data, and (v) PlantCLEF: multi-species plant identification in vegetation plot images.
ER  -