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Denoising and Motion Artifact Removal Using Deformable Kernel Prediction Neural Network for Color-Intensified CMOS.
Han, Zhenghao; Li, Li; Jin, Weiqi; Wang, Xia; Jiao, Gangcheng; Liu, Xuan; Wang, Hailin.
Afiliação
  • Han Z; Key Laboratory of Photo-Electronic Imaging Technology and Systems, School of Optics and Photonics, Ministry of Education of China, Beijing Institute of Technology, Beijing 100081, China.
  • Li L; Key Laboratory of Photo-Electronic Imaging Technology and Systems, School of Optics and Photonics, Ministry of Education of China, Beijing Institute of Technology, Beijing 100081, China.
  • Jin W; Science and Technology on Low-Light-Level Night Vision Laboratory, Xi'an 710065, China.
  • Wang X; Key Laboratory of Photo-Electronic Imaging Technology and Systems, School of Optics and Photonics, Ministry of Education of China, Beijing Institute of Technology, Beijing 100081, China.
  • Jiao G; Key Laboratory of Photo-Electronic Imaging Technology and Systems, School of Optics and Photonics, Ministry of Education of China, Beijing Institute of Technology, Beijing 100081, China.
  • Liu X; Science and Technology on Low-Light-Level Night Vision Laboratory, Xi'an 710065, China.
  • Wang H; Key Laboratory of Photo-Electronic Imaging Technology and Systems, School of Optics and Photonics, Ministry of Education of China, Beijing Institute of Technology, Beijing 100081, China.
Sensors (Basel) ; 21(11)2021 Jun 04.
Article em En | MEDLINE | ID: mdl-34200038
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Artefatos Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China 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 Assunto principal: Redes Neurais de Computação / Artefatos Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China País de publicação: Suíça