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dc.contributor.authorKhan, Amir
dc.contributor.authorAnsari, Samar
dc.date.accessioned2021-03-24T09:38:32Z
dc.date.available2021-03-24T09:38:32Z
dc.date.copyright2021
dc.date.issued2021-02-06
dc.identifier.citationKhan A., Ansari M.S. (2021) Deep Learning Based Stable and Unstable Candle Flame Detection. In: Thampi S.M., Piramuthu S., Li KC., Berretti S., Wozniak M., Singh D. (eds) Machine Learning and Metaheuristics Algorithms, and Applications. SoMMA 2020. Communications in Computer and Information Science, vol 1366. Springer, Singapore. https://doi.org/10.1007/978-981-16-0419-5_5en_US
dc.identifier.isbn9789811604188
dc.identifier.isbn9789811604195
dc.identifier.urihttp://research.thea.ie/handle/20.500.12065/3553
dc.description.abstractThis paper presents a deep learning based solution for identification of normal and abnormal candle flames, controlled and uncontrolled flames. Candle flames affected by external factors like wind, improper combustion of fuel etc. Proposed CNN based deep neural network can successfully classify the stable and unstable candle flame with an accuracy of 67% for generated test set and an accuracy of 83% for random images taken from open source on internet.en_US
dc.formatPDFen_US
dc.publisherSpringeren_US
dc.relation.ispartofMachine Learning and Metaheuristics Algorithms, and Applications.en_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectStable flameen_US
dc.subjectUnstable flameen_US
dc.subjectDeep learningen_US
dc.titleDeep learning based stable and unstable candle flame detectionen_US
dc.typeinfo:eu-repo/semantics/otheren_US
dc.contributor.affiliationAthlone Institute of Technologyen_US
dc.identifier.conferenceMachine Learning and Metaheuristics Algorithms, and Applications. Second Symposium, SoMMA 2020, Chennai, India, October 14–17, 202
dc.identifier.doi10.1007/978-981-16-0419-5_5en_US
dc.identifier.orcidhttps://orcid.org/0000-0002-4368-0478en_US
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessen_US
dc.subject.departmentSoftware Research Institute AITen_US
dc.type.versioninfo:eu-repo/semantics/acceptedVersionen_US


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Attribution-NonCommercial-NoDerivatives 4.0 International
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International