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Revolutionizing Human?Computer Interaction: Unraveling the Power of Deep Learning Convolutional Neural Networks in Face Recognition

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dc.citedby0
dc.contributor.authorBaharum A.en_US
dc.contributor.authorHalamy S.en_US
dc.contributor.authorIsmail R.en_US
dc.contributor.authorAbdul Rahim E.en_US
dc.contributor.authorMat Noor N.A.en_US
dc.contributor.authorDeris F.D.en_US
dc.contributor.authorid55916175500en_US
dc.contributor.authorid57197830951en_US
dc.contributor.authorid36080877900en_US
dc.contributor.authorid59333589000en_US
dc.contributor.authorid54791122900en_US
dc.contributor.authorid56285335200en_US
dc.date.accessioned2025-03-03T07:46:47Z
dc.date.available2025-03-03T07:46:47Z
dc.date.issued2024
dc.description.abstractFace recognition, being one of the most effective applications of image analysis, has recently received a lot of attention due to the huge implication in human?computer interaction (HCI). As the availability and eligibility to detect a person?s facial features, face recognition technology has been used in biometric detection applications as uses certain aspects of a person?s physiology to identify them. In addition, Deep Learning, under the subset of machine learning, can solve various problems, especially in image processing and face recognition. The advancement and development of Deep Learning can also enhance the use of the Convolution Neural Network (CNN) as the predominant model in the field of face recognition. The paper discusses the systems based on CNN approaches and algorithms and provides a review of the CNN face recognition approach. Furthermore, each paper?s details, such as used datasets, techniques, architecture, and obtained findings, hence the application are fully summarized and analyzed. ? The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1007/978-981-97-2977-7_13
dc.identifier.epage229
dc.identifier.scopus2-s2.0-85204401976
dc.identifier.spage213
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85204401976&doi=10.1007%2f978-981-97-2977-7_13&partnerID=40&md5=cad37c6af1910969e476168999534bf6
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/37031
dc.identifier.volume1199 LNEE
dc.pagecount16
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.sourceScopus
dc.sourcetitleLecture Notes in Electrical Engineering
dc.subjectAdversarial machine learning
dc.subjectContrastive Learning
dc.subjectDeep neural networks
dc.subjectFace recognition
dc.subjectFederated learning
dc.subjectHuman computer interaction
dc.subjectComputer interaction
dc.subjectConvolution neural network
dc.subjectConvolutional neural network
dc.subjectDeep-learning
dc.subjectFacial feature
dc.subjectImage analyze
dc.subjectImage-analysis
dc.subjectMachine-learning
dc.subjectPower
dc.subjectConvolutional neural networks
dc.titleRevolutionizing Human?Computer Interaction: Unraveling the Power of Deep Learning Convolutional Neural Networks in Face Recognitionen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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