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Selective BTEX Measurements Using Deep Neural Networks

dc.contributor.authorMhanna, Mhanna
dc.contributor.authorSy, Mohamed
dc.contributor.authorFarooq, Aamir
dc.date.accessioned2021-11-01T13:22:20Z
dc.date.available2021-11-01T13:22:20Z
dc.date.issued2021
dc.identifier.citationMhanna, 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.49
dc.identifier.isbn978-1-6654-4792-8
dc.identifier.issn2160-8989
dc.identifier.doi10.1364/cleo_at.2021.jth3a.49
dc.identifier.urihttp://hdl.handle.net/10754/673059
dc.description.abstractA 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.
dc.publisherIEEE
dc.relation.urlhttps://ieeexplore.ieee.org/document/9573171/
dc.relation.urlhttps://ieeexplore.ieee.org/document/9573171/
dc.relation.urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9573171
dc.rightsArchived with thanks to IEEE
dc.titleSelective BTEX Measurements Using Deep Neural Networks
dc.typeConference Paper
dc.contributor.departmentChemical Kinetics & Laser Sensors Laboratory
dc.contributor.departmentClean Combustion Research Center
dc.contributor.departmentKing Abdullah University of Science and Technology (KAUST),hysical Science and Engineering Division,Thuwal,Saudi Arabia,23955-6900
dc.contributor.departmentMechanical Engineering
dc.contributor.departmentMechanical Engineering Program
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.conference.date9-14 May 2021
dc.conference.name2021 Conference on Lasers and Electro-Optics (CLEO)
dc.conference.locationSan Jose, CA, USA
dc.eprint.versionPost-print
kaust.personMhanna, Mhanna
kaust.personSy, Mohamed
kaust.personFarooq, Aamir
refterms.dateFOA2021-11-14T05:57:53Z


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