Title:	Overview of SnakeCLEF 2021: Automatic snake species identification with country-level focus
Authors:	Picek, Lukáš Durso, Andrew M. Bolon, Isabelle de Castañeda, Rafael Ruiz
Citation:	PICEK, L. DURSO, AM. BOLON, I. DE CASTAÑEDA, RR. Overview of SnakeCLEF 2021: Automatic snake species identification with country-level focus. In Proceedings of the Working Notes of CLEF 2021 - Conference and Labs of the Evaluation Forum. Bucharest: CEUR-WS, 2021. s. 1463-1476. ISBN: neuvedeno , ISSN: 1613-0073
Issue Date:	2021
Publisher:	CEUR-WS
Document type:	konferenční příspěvek ConferenceObject
URI:	2-s2.0-85113525880 http://hdl.handle.net/11025/47274
ISBN:	neuvedeno
ISSN:	1613-0073
Keywords in different language:	Biodiversity;Birds;Conservation;Geographical distribution;Historic preservation;Machine learning;Remote sensing
Abstract in different language:	A robust and accurate AI-driven system as an assistance tool for snake species identification has vast potential to help lower deaths and disabilities caused by snakebites. With that in mind, we prepared the SnakeCLEF 2021: Automatic Snake Species Identification Challenge with Country-Level Focus, designed to provide an evaluation platform that can help track the performance of end-to-end AI-driven snake species recognition systems with a focus on overall country-wise performance. We have provided 386,006 photographs of 772 snake species collected in 188 countries and country-species presence mapping for the challenge. In this paper, we report 1) a description of the provided data, 2) evaluation methodology and principles, 3) an overview of the systems submitted by the participating teams, and 4) a discussion of the obtained results.
Rights:	© authors
Appears in Collections:	Konferenční příspěvky / Conference Papers (KKY) OBD

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