A deep-learning-based workflow to assess taxonomic affinity of hominid teeth with a test on discriminating Pongo and Homo upper molars.

Journal: American journal of physical anthropology
PMID: 33860534

Abstract

OBJECTIVES: Convolutional neural network (CNN) is a state-of-art deep learning (DL) method with superior performance in image classification. Here, a CNN-based workflow is proposed to discriminate hominid teeth. Our hope is that this method could help confirm otherwise questionable records of Homo from Pleistocene deposits where there is a standing risk of mis-attributing molars of Pongo to Homo.

Authors

  • Zhixing Yi
    Institute of Cultural Heritage, Shandong University, Qingdao, China.
  • ClĂ©ment Zanolli
    Laboratoire PACEA, UMR 5199 CNRS, Université de Bordeaux, Pessac, France.
  • Wei Liao
    Department of Surgery, Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Wei Wang
    State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.

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