PENGENALAN WAJAH TERSAMAR MENGGUNAKAN CONVOLUTION NEURAL NETWORK DAN SUPPORT VECTOR MACHINE

CAROLIN, SELLY and Ubaya, Huda (2022) PENGENALAN WAJAH TERSAMAR MENGGUNAKAN CONVOLUTION NEURAL NETWORK DAN SUPPORT VECTOR MACHINE. Undergraduate thesis, Sriwijaya University.

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Abstract

In recent decades, facial recognition systems have been the subject of frequent research in the field of computer vision. The system has been used in several fields, such as smartphones for face locking, immigration. A disguised face is a face that cannot be recognized by others. For example, criminals may intentionally try to hide their identity by using external disguise accessories (such as sunglasses or masks). The deep learning method used in this research is Convolutional Neural Networks (CNN) and face classification using Support Vector Machine (SVM). The system uses 1000 data consisting of 10 people with a training and testing ratio of 8:2. From the results of testing the system on the data, the accuracy is 98.4%, precision is 0.96, recall is 0.965 and F1-score is 0.961.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Pengenalan Wajah, Wajah Tersamar, Deep Learning, Convolution Neural Network (CNN), Support Vector Machine (SVM)
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Selly Carolin
Date Deposited:	21 Nov 2022 08:44
Last Modified:	21 Nov 2022 08:44
URI:	http://repository.unsri.ac.id/id/eprint/82362

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