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Overview of SnakeCLEF 2021: Automatic snake species identification with country-level focus
Conference proceeding

Overview of SnakeCLEF 2021: Automatic snake species identification with country-level focus

Lukáš Picek, Andrew M. Durso, Isabelle Bolon and Rafael Ruiz Castañeda
01-01-2021

Abstract

Geographical distribution Historic preservation Machine learning Conservation Birds Biodiversity Remote sensing
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.

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UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

#3 Good Health and Well-Being
#15 Life on Land

Source: SDGs in the Output

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