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Enhancing biomechanical machine learning with limited data: generating realistic synthetic posture data using generative artificial intelligence.
Dindorf, Carlo; Dully, Jonas; Konradi, Jürgen; Wolf, Claudia; Becker, Stephan; Simon, Steven; Huthwelker, Janine; Werthmann, Frederike; Kniepert, Johanna; Drees, Philipp; Betz, Ulrich; Fröhlich, Michael.
Afiliação
  • Dindorf C; Department of Sports Science, University of Kaiserslautern-Landau, Kaiserslautern, Germany.
  • Dully J; Department of Sports Science, University of Kaiserslautern-Landau, Kaiserslautern, Germany.
  • Konradi J; Institute of Physical Therapy, Prevention and Rehabilitation, University Medical Centre, Johannes Gutenberg University Mainz, Mainz, Germany.
  • Wolf C; Institute of Physical Therapy, Prevention and Rehabilitation, University Medical Centre, Johannes Gutenberg University Mainz, Mainz, Germany.
  • Becker S; Department of Sports Science, University of Kaiserslautern-Landau, Kaiserslautern, Germany.
  • Simon S; Department of Sports Science, University of Kaiserslautern-Landau, Kaiserslautern, Germany.
  • Huthwelker J; Institute of Physical Therapy, Prevention and Rehabilitation, University Medical Centre, Johannes Gutenberg University Mainz, Mainz, Germany.
  • Werthmann F; Department of Orthopedics and Trauma Surgery, University Medical Centre, Johannes Gutenberg University Mainz, Mainz, Germany.
  • Kniepert J; Department of Orthopedics and Trauma Surgery, University Medical Centre, Johannes Gutenberg University Mainz, Mainz, Germany.
  • Drees P; Department of Orthopedics and Trauma Surgery, University Medical Centre, Johannes Gutenberg University Mainz, Mainz, Germany.
  • Betz U; Institute of Physical Therapy, Prevention and Rehabilitation, University Medical Centre, Johannes Gutenberg University Mainz, Mainz, Germany.
  • Fröhlich M; Department of Sports Science, University of Kaiserslautern-Landau, Kaiserslautern, Germany.
Front Bioeng Biotechnol ; 12: 1350135, 2024.
Article em En | MEDLINE | ID: mdl-38419724
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Bioeng Biotechnol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Alemanha País de publicação: Suíça
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Bioeng Biotechnol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Alemanha País de publicação: Suíça