Open AccessAn Effective Implementation of Face Recognition Using Deep Convolutional Network
Author(s) -
Hayder Najm,
Hayder Ansaf,
Oday A. Hassen
Publication year - 2019
Publication title -
xi'nan jiaotong daxue xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.308
H-Index - 21
ISSN - 0258-2724
DOI - 10.35741/issn.0258-2724.54.5.29
Subject(s) - computer science , convolutional neural network , artificial intelligence , facial recognition system , face (sociological concept) , identification (biology) , deep learning , analytics , domain (mathematical analysis) , machine learning , pattern recognition (psychology) , domain knowledge , data science , mathematical analysis , social science , botany , mathematics , sociology , biology
Human Face Recognition for forensic investigations and e-governance is widely adopted so that the specific face points can be trained and further investigations can be done. In this approach, the key points of human face with the dynamic features are extracted and trained in the deep neural network model so that the intrinsic aspects of the human face can be realized and further can be used for the criminal investigation or social analytics based applications. In this research manuscript, the usage of deep learning based convolutional network is integrated for the human face analytics and recognition for diversified applications. It is done to have the cavernous evaluation patterns in multiple domains for the knowledge discovery and predictive features of the human face identification domain.