Název: | Overview of SnakeCLEF 2022: Automated Snake Species Identification on a Global Scale |
Autoři: | Picek, Lukáš Hrúz, Marek Durso, Andrew M. Bolon, Isabelle |
Citace zdrojového dokumentu: | PICEK, L. HRÚZ, M. DURSO, AM. BOLON, I. Overview of SnakeCLEF 2022: Automated Snake Species Identification on a Global Scale. In Proceedings of the Working Notes of CLEF 2022 - Conference and Labs of the Evaluation Forum. Bologna: CEUR-WS, 2022. s. 1957-1969. ISBN: neuvedeno , ISSN: 1613-0073 |
Datum vydání: | 2022 |
Nakladatel: | CEUR-WS |
Typ dokumentu: | konferenční příspěvek ConferenceObject |
URI: | 2-s2.0-85136952391 http://hdl.handle.net/11025/51465 |
ISBN: | neuvedeno |
ISSN: | 1613-0073 |
Klíčová slova v dalším jazyce: | benchmark;biodiversity;classification;computer vision;epidemiology;fine grained visual categorization;global health;LifeCLEF;machine learning;reptile;snake;snake bite;SnakeCLEF;species identification |
Abstrakt v dalším jazyce: | The main goal of the third year of the SnakeCLEF challenge was to provide an evaluation platform that helps track the performance of AI-driven methods for snake species recognition systems on a global scale and allows direct comparison with human experts. We ran two challenges separately for humans — experts and novices — and AI methods in order to lay the groundwork for future comparison between human and machine-based snake species identification. We have provided 187,129 snake observations with 318,532 photographs — 270,251 for training and 48,281 for testing — of 1,572 snake species collected in 208 countries. The human performance evaluation was conducted on a tailored subset with 150 images derived from the full test set. We report (i) a description of the provided data, (ii) evaluation methodology and principles, (iii) an overview of the methods submitted by the participating teams, and (iv) a discussion of the obtained results. © 2022 Copyright for this paper by its authors. |
Práva: | © authors |
Vyskytuje se v kolekcích: | Konferenční příspěvky / Conference papers (NTIS) Konferenční příspěvky / Conference Papers (KKY) OBD |
Soubory připojené k záznamu:
Soubor | Velikost | Formát | |
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Picek_Overview_of_SnakeCLEF2022.pdf | 14,28 MB | Adobe PDF | Zobrazit/otevřít |
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http://hdl.handle.net/11025/51465
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