Smart Fatigue Monitoring using RF Sensing Employing a Deep Learning Convolutional Neural Network

Cooper, J. , Taylor, W. , Imran, M. and Abbasi, Q. (2024) Smart Fatigue Monitoring using RF Sensing Employing a Deep Learning Convolutional Neural Network. In: 2024 IEEE International Symposium on Antennas and Propagation and ITNC-USNC-URSI Radio Science Meeting, Florence, Italy, 14-19 July 2024, (Accepted for Publication)

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Item Type:Conference Proceedings
Additional Information:This work was supported in parts by Engineering and Physical Sciences Research Council (EPSRC) grants EP/T021020/1 and EP/W003228/1.
Status:Accepted for Publication
Refereed:Yes
Glasgow Author(s) Enlighten ID:Imran, Professor Muhammad and Cooper, Professor Jonathan and Abbasi, Professor Qammer and Taylor, William
Authors: Cooper, J., Taylor, W., Imran, M., and Abbasi, Q.
College/School:College of Science and Engineering
College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
College of Science and Engineering > School of Engineering > Biomedical Engineering
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
307829Quantum-Inspired Imaging for Remote Monitoring of Health & Disease in Community HealthcareJonathan CooperEngineering and Physical Sciences Research Council (EPSRC)EP/T021020/1ENG - Biomedical Engineering