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An algorithm competition for automatic species identification from herbarium specimens.
Applications in Plant Sciences ( IF 3.6 ) Pub Date : 2020-07-01 , DOI: 10.1002/aps3.11365 Damon P Little 1 , Melissa Tulig 1 , Kiat Chuan Tan 2 , Yulong Liu 2, 3 , Serge Belongie 2, 4 , Christine Kaeser-Chen 2 , Fabián A Michelangeli 1 , Kiran Panesar 5 , R V Guha 5 , Barbara A Ambrose 1
Applications in Plant Sciences ( IF 3.6 ) Pub Date : 2020-07-01 , DOI: 10.1002/aps3.11365 Damon P Little 1 , Melissa Tulig 1 , Kiat Chuan Tan 2 , Yulong Liu 2, 3 , Serge Belongie 2, 4 , Christine Kaeser-Chen 2 , Fabián A Michelangeli 1 , Kiran Panesar 5 , R V Guha 5 , Barbara A Ambrose 1
Affiliation
Plant biodiversity is threatened, yet many species remain undescribed. It is estimated that >50% of undescribed species have already been collected and are awaiting discovery in herbaria. Robust automatic species identification algorithms using machine learning could accelerate species discovery.
中文翻译:
从植物标本中自动识别物种的算法竞赛。
植物生物多样性受到威胁,但许多物种仍未被描述。据估计,已经收集了超过 50% 的未描述物种,正在植物标本室中等待发现。使用机器学习的强大的自动物种识别算法可以加速物种发现。
更新日期:2020-07-01
中文翻译:
从植物标本中自动识别物种的算法竞赛。
植物生物多样性受到威胁,但许多物种仍未被描述。据估计,已经收集了超过 50% 的未描述物种,正在植物标本室中等待发现。使用机器学习的强大的自动物种识别算法可以加速物种发现。