PENGENALAN WAJAH SECARA REALTIME MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK PADA CITRA MULTI-FACE

SUSANTO, ARI and Fachrurrozi, Muhammad and Erwin, Erwin (2019) PENGENALAN WAJAH SECARA REALTIME MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK PADA CITRA MULTI-FACE. Undergraduate thesis, Sriwijaya University.

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Abstract

This research is about realtime face recognition using convolutional neural network. In this research uses two convolutional neural network architectures, VGG16 and a simple convolutional neural network architecture consisting of two convolutional layers, one pooling layer, and two fully connected layers. The VGG16 architecture consists of 13 convolutional layers, 5 pooling layers, 2 fully connected layers. Offline testing is performed on AT & T Face Database and get an accuracy value of 95% on the Simple Convolutional Neural Network architecture and the accuracy obtained using VGG16 architecture is 98%. The test was also carried out offline and in realtime using data from 11 Informatics Engineering students at Sriwijaya University. Offline testing gets an accuracy of 99% using the Simple Convolutional Neural Network and an accuracy of 98% using the VGG16 architecture. For realtime testing accuracy value is 86% with an average respond time of 0.4 seconds using VGG16 architecture and 70% of accuracy with an average respond time of 0.02 seconds using the Simple Convolutional Neural Network architecture.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Face recognition, deep learning, convolutional neural network
Subjects:	Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA75.5.A142 Computer science. Information society. Information technology. R Medicine > R Medicine (General) > R858-859.7 Computer applications to medicine. Medical informatics
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Users 3053 not found.
Date Deposited:	14 Nov 2019 07:57
Last Modified:	14 Nov 2019 07:57
URI:	http://repository.unsri.ac.id/id/eprint/16269

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