SISTEM PENGENALAN WAJAH SECARA REAL TIME MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK DAN SUPPORT VECTOR MACHINE

ALFIANSYAH, ALFIANSYAH and Siswanti, Sri Desy and Ubaya, Huda (2020) SISTEM PENGENALAN WAJAH SECARA REAL TIME MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK DAN SUPPORT VECTOR MACHINE. Undergraduate thesis, Sriwijaya University.

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Abstract

Face recognition system is a branch of biometric science that is useful for identifying someone based on their physical characteristics, in this case their face. In general, face recognition system consists of three stages, face detection, feature extraction and face recognition. In this study Multi Task Cascade Convolutional Neural Network was used for the face detection process, then VGGFace for the feature extraction process and Support Vector Machine for the classification process. The system is trained and tested using 1000 data from 10 different people with a comparison of 8: 2 training and test data. From the results of the system testing of the data, the system accuracy is 98% with 38s processing time. Then from the results of realtime system testing, the accuracy of the system is 96.67% with an average processing time of 0.155s per data.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Sistem pengenalan wajah, Real Time, Multi Task Cascade Convolutional Neural Network, VGGFace, Support Vector Machine
Subjects: T Technology > T Technology (General) > T1-995 Technology (General)
Divisions: 09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User: Alfiansyah Alfiansyah
Date Deposited: 12 Jan 2021 02:39
Last Modified: 12 Jan 2021 02:39
URI: http://repository.unsri.ac.id/id/eprint/39709

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