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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Detalhes bibliográficos
Autor principal: Cao, Yongjie (author)
Outros Autores: 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)
Formato: article
Idioma:eng
Publicado em: 2022
Assuntos:
Forensic sciences
forensic anthropology
sex estimation
pelvis
deep learning
convolutional neural network
Texto completo:http://hdl.handle.net/10316/101044
País:Portugal
Oai:oai:estudogeral.sib.uc.pt:10316/101044

Texto Completo

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

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