Tire Speckle Interference Bubble Defect Detection Based on Improved Faster RCNN-FPN.

Yang, Shihao; Jiao, Dongmei; Wang, Tongkun; He, Yan

Yang, Shihao; Jiao, Dongmei; Wang, Tongkun; He, Yan.

Afiliação

Yang S; College of Mechanical and Electrical Engineering, Qingdao University of Science and Technology, Qingdao 266061, China.
Jiao D; College of Mechanical and Electrical Engineering, Qingdao University of Science and Technology, Qingdao 266061, China.
Wang T; College of Mechanical and Electrical Engineering, Qingdao University of Science and Technology, Qingdao 266061, China.
He Y; College of Mechanical and Electrical Engineering, Qingdao University of Science and Technology, Qingdao 266061, China.

Sensors (Basel) ; 22(10)2022 May 21.

Article em En | MEDLINE | ID: mdl-35632316

Palavras-chave

computer vision; deep learning; feature pyramid network; object detection; tire defect detection

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

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