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dc.contributor.authorYurtdaş, Gözde
dc.contributor.authorAlhajj, Loubaba
dc.contributor.authorSailunaz, Kashfia
dc.contributor.authorÖzyer, Tansel
dc.contributor.authorRokne, Jon
dc.contributor.authorAlhajj, Reda
dc.date.accessioned2024-05-23T05:26:50Z
dc.date.available2024-05-23T05:26:50Z
dc.date.issued2023en_US
dc.identifier.citationYurtdaş, G., Alhajj, L., Sailunaz, K., Özyer, T., Rokne, J. ve Alhajj, R. (2023). Creating a learning profile by using face and emotion recognition. 15th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM içinde (551-557. ss.). Kuşadası, Turkey, November 6-9, 2023. http://dx.doi.org/10.1145/3625007.3627339en_US
dc.identifier.isbn9798400704093
dc.identifier.issn2473-9928
dc.identifier.issn2473-991X
dc.identifier.urihttp://dx.doi.org/10.1145/3625007.3627339
dc.identifier.urihttps://hdl.handle.net/20.500.12511/12486
dc.description.abstractThe aim of this work is to employ face recognition for creating learning profiles of the analysed persons who are students in this study. Generating education profiles will help experts in the diagnosis of Attention Deficit Hyperactivity Disorder (ADHD), which is a serious problem in children. Children with ADHD often have the ability and potential to learn. However, it may be difficult to reveal their capabilities and skills. Accordingly, a suffering child may have a hard time succeeding in real life when he/she is ignored and expected to mix with other children. The unrealized gap and deficiency may lead to other problems and more complicated situation with unpredictable consequences. Thanks to the system developed in this study, and the like, which will help in diagnosing the ADHD disease, and hence suffering individuals will be able to recognize their deficiencies, understand their ability to learn and adapt when approached differently in a way which suits his/her situation. This personalized handling of infected students will be an excellent guide to advance their potential and integration within the society carefully and smoothly. The system analyzes the face of a student to inspire his/her emotional state. The reported test results demonstrate how the system works well and produces high accuracy under a variety of severe conditions such as skewed angle, less illumination, accessories etc.en_US
dc.description.sponsorshipACM SIGKDD. Association for Computing Machinery (ACM). et al. IEEE. IEEE Computer Society. IEEE TCDE.en_US
dc.language.isoengen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution International 4.0*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectAttention Deficit Hyperactivity Disorderen_US
dc.subjectEmotion Detectionen_US
dc.subjectFace Recognitionen_US
dc.subjectLearning Profileen_US
dc.titleCreating a learning profile by using face and emotion recognitionen_US
dc.typeconferenceObjecten_US
dc.relation.ispartof15th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAMen_US
dc.departmentİstanbul Medipol Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.authorid0009-0000-0909-0274en_US
dc.authorid0000-0001-6657-9738en_US
dc.identifier.startpage551en_US
dc.identifier.endpage557en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1145/3625007.3627339en_US
dc.institutionauthorYurtdaş, Gözde
dc.institutionauthorAlhajj, Loubaba
dc.institutionauthorAlhajj, Reda
dc.identifier.wos001191293500088en_US
dc.identifier.scopus2-s2.0-85190625622en_US


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