Improving accuracy of contactless respiratory rate estimation by enhancing thermal sequences with deep neural_networks

HIGHLIGHTS

• who: Alicja Kwasniewska et al. from the Department of Biomedical Engineering, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gabriela Narutowicza, Gdansk, Poland have published the article: Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural_Networks, in the Journal: (JOURNAL)
• what: To avoid being biased by a specific method and data, in this study, the authors extend the experiments to different RR estimators and evaluate the proposed solution on two thermal datasets collected by the authors for 71 volunteers. The authors evaluate two respiratory rate estimators proposed and . . .
  

   

  

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