Ping Huang
AuthID: R-00J-SFZ
1
TITLE: DiatomNet v1.0: A novel approach for automatic diatom testing for drowning diagnosis in forensically biomedical application Full Text
AUTHORS: Zhang, Ji; Vieira, Duarte Nuno; Cheng, Qi; Zhu, Yongzheng; Deng, Kaifei; Zhang, Jianhua; Qin, Zhiqiang; Sun, Qiran; Zhang, Tianye; Ma, Kaijun; Zhang, Xiaofeng; Huang, Ping;
PUBLISHED: 2023, SOURCE: COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, VOLUME: 232
AUTHORS: Zhang, Ji; Vieira, Duarte Nuno; Cheng, Qi; Zhu, Yongzheng; Deng, Kaifei; Zhang, Jianhua; Qin, Zhiqiang; Sun, Qiran; Zhang, Tianye; Ma, Kaijun; Zhang, Xiaofeng; Huang, Ping;
PUBLISHED: 2023, SOURCE: COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, VOLUME: 232
INDEXED IN: 
Scopus 
WOS
Scopus WOS2
TITLE: An efficient method for building a database of diatom populations for drowning site inference using a deep learning algorithm Full Text
AUTHORS: Zhang, J; Zhou, YY; Vieira, DN; Cao, YJ; Deng, KF; Cheng, Q; Zhu, YZ; Zhang, JH; Qin, ZQ; Ma, KJ; Chen, YJ; Huang, P;
PUBLISHED: 2021, SOURCE: INTERNATIONAL JOURNAL OF LEGAL MEDICINE
AUTHORS: Zhang, J; Zhou, YY; Vieira, DN; Cao, YJ; Deng, KF; Cheng, Q; Zhu, YZ; Zhang, JH; Qin, ZQ; Ma, KJ; Chen, YJ; Huang, P;
PUBLISHED: 2021, SOURCE: INTERNATIONAL JOURNAL OF LEGAL MEDICINE
INDEXED IN: Scopus WOS
Scopus WOS3
TITLE: Use of deep learning in forensic sex estimation of virtual pelvic models from the Han population
AUTHORS: Cao, YJ; Ma, YG; Yang, XT; Xiong, J; Wang, YH; Zhang, JH; Qin, ZQ; Chen, YJ; Vieira, DN; Chen, F; Zhang, J; Huang, P;
PUBLISHED: 2021, SOURCE: FORENSIC SCIENCES RESEARCH
AUTHORS: Cao, YJ; Ma, YG; Yang, XT; Xiong, J; Wang, YH; Zhang, JH; Qin, ZQ; Chen, YJ; Vieira, DN; Chen, F; Zhang, J; Huang, P;
PUBLISHED: 2021, SOURCE: FORENSIC SCIENCES RESEARCH
INDEXED IN: Scopus WOS
Scopus WOS