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dc.contributor.authorBazrafkan, Shabab
dc.contributor.authorNedelcu, Tudor
dc.contributor.authorFilipczuk, Pawel
dc.contributor.authorCorcoran, Peter
dc.date.accessioned2021-04-07T14:00:15Z
dc.date.available2021-04-07T14:00:15Z
dc.date.issued2017-01-08
dc.identifier.citationBazrafkan, Shabab, Nedelcu, Tudor, Filipczuk, Pawel, & Corcoran, Peter. (2017). Deep learning for facial expression recognition: A step closer to a smartphone that knows your moods. Paper presented at the 2017 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, USA, 08-10 January.en_IE
dc.identifier.urihttp://hdl.handle.net/10379/16688
dc.description.abstractBy growing the capacity and processing power of the handheld devices nowadays, a wide range of capabilities can be implemented in these devices to make them more intelligent and user friendly. Determining the mood of the user can be used in order to provide suitable reactions from the device in different conditions. One of the most studied ways of mood detection is by using facial expressions, which is still one of the challenging fields in pattern recognition and machine learning science.Deep Neural Networks (DNN) have been widely used in order to overcome the difficulties in facial expression classification. In this paper it is shown that the classification accuracy is significantly lower when the network is trained with one database and tested with a different database. A solution for obtaining a general and robust network is given as well.en_IE
dc.description.sponsorshipThis research is funded under the SFI Strategic Partnership Program by Science Foundation Ireland (SFI) and FotoNation Ltd. Project ID: 13/SPP/I2868 on Next Generation Imaging for Smartphone and Embedded Platforms. This work is supported by the Enterprise Partnership Scheme program of the Irish Research Councilen_IE
dc.formatapplication/pdfen_IE
dc.language.isoenen_IE
dc.publisherInstitute of Electrical and Electronics Engineersen_IE
dc.relation.ispartof2017 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS (ICCE)en
dc.subjectfacial expression recognitionen_IE
dc.subjectsmartphoneen_IE
dc.subjectmoodsen_IE
dc.titleDeep learning for facial expression recognition: A step closer to a smartphone that knows your moodsen_IE
dc.typeConference Paperen_IE
dc.date.updated2021-04-02T17:31:27Z
dc.identifier.doi10.1109/ICCE.2017.7889290
dc.local.publishedsourcehttps://dx.doi.org/10.1109/ICCE.2017.7889290en_IE
dc.description.peer-reviewedpeer-reviewed
dc.contributor.funderScience Foundation Irelanden_IE
dc.contributor.funderFotoNation Limiteden_IE
dc.contributor.funderIrish Research Councilen_IE
dc.internal.rssid16220941
dc.local.contactPeter Corcoran, Electrical & Electronic Eng, Room 3041, Engineering Building, Nui Galway. 2764 Email: peter.corcoran@nuigalway.ie
dc.local.copyrightcheckedYes
dc.local.versionACCEPTED
dcterms.projectinfo:eu-repo/grantAgreement/SFI/SFI Strategic Partnership Programme/13/SPP/I2868/IE/Next Generation Imaging for Smartphone and Embedded Platforms/en_IE
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