A challenge of deep-learning-based object detection for hair follicle dataset.

Lv, Wei; Chen, Tao; Zeng, Yifan; Liu, Weihong; Huang, Chuying

Lv, Wei; Chen, Tao; Zeng, Yifan; Liu, Weihong; Huang, Chuying.

Afiliação

Lv W; Department of Alibaba Cloud Big Data Application, Zhuhai College of Science and Technology, Zhuhai, China.
Chen T; Department of Alibaba Cloud Big Data Application, Zhuhai College of Science and Technology, Zhuhai, China.
Zeng Y; Department of Alibaba Cloud Big Data Application, Zhuhai College of Science and Technology, Zhuhai, China.
Liu W; Department of Alibaba Cloud Big Data Application, Zhuhai College of Science and Technology, Zhuhai, China.
Huang C; Department of Alibaba Cloud Big Data Application, Zhuhai College of Science and Technology, Zhuhai, China.

J Cosmet Dermatol ; 22(9): 2565-2578, 2023 Sep.

Article em En | MEDLINE | ID: mdl-37021716

Assuntos

Aprendizado Profundo; Folículo Piloso; Feminino; Humanos; Masculino; Cabelo; Algoritmos; Alopecia/diagnóstico por imagem

Palavras-chave

CNN; YOLOv5; deep learning; hair follicle dataset; object detection

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Folículo Piloso / Aprendizado Profundo Tipo de estudo: Diagnostic_studies Limite: Female / Humans / Male Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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