Use of deep learning in forensic sex estimation of virtual pelvic models from the Han population

Accurate sex estimation is crucial to determine the identity of human skeletal remains effectively. Here, we developed convolutional neural network (CNN) models for sex estimation on virtual hemi-pelvic regions, including the ventral pubis (VP), dorsal pubis (DP), greater sciatic notch (GSN), pelvic...

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Bibliographic Details
Main Author: Cao, Yongjie (author)
Other Authors: Ma, Yonggang (author), Yang, Xiaotong (author), Xiong, Jian (author), Wang, Yahui (author), Zhang, Jianhua (author), Qin, Zhiqiang (author), Chen, Yijiu (author), Vieira, Duarte Nuno (author), Chen, Feng (author), Zhang, Ji (author), Huang, Ping (author)
Format: article
Language:eng
Published: 2022
Subjects:
Forensic sciences
forensic anthropology
sex estimation
pelvis
deep learning
convolutional neural network
Online Access:http://hdl.handle.net/10316/101044
Country:Portugal
Oai:oai:estudogeral.sib.uc.pt:10316/101044

Internet

http://hdl.handle.net/10316/101044

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