Abstract
Building accurate knowledge of the identity, the geographic distribution and the evolution of living species is essential for a sustainable development of humanity, as well as for biodiversity conservation. Unfortunately, such basic information is often only partially available for professional stakeholders, teachers, scientists and citizens, and often incomplete for ecosystems that possess the highest diversity. In this context, an ultimate ambition is to set up innovative information systems relying on the automated identification and understanding of living organisms as a means to engage massive crowds of observers and boost the production of biodiversity and agro-biodiversity data. The LifeCLEF 2018 initiative proposes three data-oriented challenges related to this vision, in the continuity of the previous editions, but with several consistent novelties intended to push the boundaries of the state-of-the-art in several research directions. This paper describes the methodology of the conducted evaluations as well as the synthesis of the main results and lessons learned.
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Acknowledgements
The organization of LifeCLEF 2018 was supported by the French project Floris’Tic (Tela Botanica, INRIA, CIRAD, INRA, IRD) funded in the context of the national investment program PIA. The organization of the BirdCLEF task was supported by the Xeno-Canto foundation for nature sounds as well as the French CNRS project SABIOD.ORG and EADM GDR CNRS MADICS, BRILAAM STIC-AmSud. The annotations of some soundscape were prepared with regreted wonderful Lucio Pando at Explorama Lodges, with the support of Pam Bucur, Marie Trone and H. Glotin.
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Joly, A. et al. (2018). Overview of LifeCLEF 2018: A Large-Scale Evaluation of Species Identification and Recommendation Algorithms in the Era of AI. In: Bellot, P., et al. Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2018. Lecture Notes in Computer Science(), vol 11018. Springer, Cham. https://doi.org/10.1007/978-3-319-98932-7_24
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