Selective BTEX Measurements Using Deep Neural Networks
Type
Conference Paper
KAUST Department
Chemical Kinetics & Laser Sensors LaboratoryClean Combustion Research Center
King Abdullah University of Science and Technology (KAUST),hysical Science and Engineering Division,Thuwal,Saudi Arabia,23955-6900
Mechanical Engineering
Mechanical Engineering Program
Physical Science and Engineering (PSE) Division
Date
2021Permanent link to this record
http://hdl.handle.net/10754/673059Metadata
Show full item recordAbstract
A laser sensor is developed for selective and simultaneous BTEX measurements. It is based on a DFB-ICL near 3.3 µm and deep neural networks (DNNs) to differentiate broad absorbance spectra of BTEX species.Citation
Mhanna, M., Sy, M., & Farooq, A. (2021). Selective BTEX Measurements Using Deep Neural Networks. Conference on Lasers and Electro-Optics. doi:10.1364/cleo_at.2021.jth3a.49Publisher
IEEEConference/Event name
2021 Conference on Lasers and Electro-Optics (CLEO)ISBN
978-1-6654-4792-8Additional Links
https://ieeexplore.ieee.org/document/9573171/https://ieeexplore.ieee.org/document/9573171/
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9573171