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STMS-YOLOv5: A Lightweight Algorithm for Gear Surface Defect Detection.
Yan, Rui; Zhang, Rangyong; Bai, Jinqiang; Hao, Huijuan; Guo, Wenjie; Gu, Xiaoyan; Liu, Qi.
Afiliación
  • Yan R; Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China.
  • Zhang R; Shandong Provincial Key Laboratory of Computer Networks, Shandong Fundamental Research Center for Computer Science, Jinan 250014, China.
  • Bai J; Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China.
  • Hao H; Shandong Provincial Key Laboratory of Computer Networks, Shandong Fundamental Research Center for Computer Science, Jinan 250014, China.
  • Guo W; Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China.
  • Gu X; Shandong Provincial Key Laboratory of Computer Networks, Shandong Fundamental Research Center for Computer Science, Jinan 250014, China.
  • Liu Q; Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China.
Sensors (Basel) ; 23(13)2023 Jun 28.
Article en En | MEDLINE | ID: mdl-37447840
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Industrias Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Industrias Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza