Hand gesture recognition for interactive media player using CNN and image classification

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dc.contributor.authorAwad, Anwar Diyaa
dc.contributor.authorKoyuncu, Hakan
dc.date.accessioned2022-12-23T10:31:59Z
dc.date.available2022-12-23T10:31:59Z
dc.date.issued2022en_US
dc.departmentEnstitüler, Lisansüstü Eğitim Enstitüsü, Elektrik ve Bilgisayar Mühendisliği Ana Bilim Dalıen_US
dc.description.abstractIn this paper the problem of gesture recognition is addressed with a focus on the recognition of handshapes. Due to the number of parameters to be considered (joint angles, hand position, three-dimensional orientation, as well as muscle and skin deformations), even the isolated problem of handshapes recognition becomes very complicated for a solution using conventional deterministic algorithms. Machine learning methods. In this paper, we evaluated the 26 signs of the Sign Language but the results can then be extended to any gesture or movement performed with only one hand. Certainly, even if these gestures can be recognized precisely.en_US
dc.identifier.citationAwad, A. D., Koyuncu, H. (2022). Hand gesture recognition for interactive media player using CNN and image classification. In 2022 International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 753-756). IEEE.en_US
dc.identifier.endpage756en_US
dc.identifier.isbn9781665470131
dc.identifier.scopus2-s2.0-85142837748
dc.identifier.scopusqualityN/A
dc.identifier.startpage753en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12939/3144
dc.indekslendigikaynakScopus
dc.institutionauthorAwad, Anwar Diyaa
dc.institutionauthorKoyuncu, Hakan
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofISMSIT 2022 - 6th International Symposium on Multidisciplinary Studies and Innovative Technologies, Proceedings
dc.relation.isversionof10.1109/ISMSIT56059.2022.9932839en_US
dc.relation.publicationcategoryKonferans Öğesi - Ulusal - İdari Personel ve Öğrencien_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAlgorithmsen_US
dc.subjectClassificationen_US
dc.subjectHand Gestureen_US
dc.subjectMachine Learningen_US
dc.titleHand gesture recognition for interactive media player using CNN and image classification
dc.typeConference Object

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