AGE AND GENDER CLASSIFIER USING DEEP NEURAL NETWORK

TEDJORAHARDJO, JOSEPH CHRISTIAN (2023) AGE AND GENDER CLASSIFIER USING DEEP NEURAL NETWORK. Other thesis, UNIVERSITAS KHATOLIK SOEGIJAPRANATA.

Preview	Text 18.K1.0015-OSEPH CHRISTIAN TEDJORAHARDJO-COVER_a.pdf Download (956kB) | Preview
	Text 18.K1.0015-OSEPH CHRISTIAN TEDJORAHARDJO-BAB I_a.pdf Restricted to Registered users only Download (157kB)
	Text 18.K1.0015-OSEPH CHRISTIAN TEDJORAHARDJO-BAB II_a.pdf Restricted to Registered users only Download (141kB)
	Text 18.K1.0015-OSEPH CHRISTIAN TEDJORAHARDJO-BAB III_a.pdf Restricted to Registered users only Download (503kB)
	Text 18.K1.0015-OSEPH CHRISTIAN TEDJORAHARDJO-BAB IV_a.pdf Restricted to Registered users only Download (20MB)
	Text 18.K1.0015-OSEPH CHRISTIAN TEDJORAHARDJO-BAB V_a.pdf Restricted to Registered users only Download (127kB)
Preview	Text 18.K1.0015-OSEPH CHRISTIAN TEDJORAHARDJO-DAPUS_a.pdf Download (154kB) | Preview
	Text 18.K1.0015-OSEPH CHRISTIAN TEDJORAHARDJO-LAMP_a.pdf Restricted to Registered users only Download (250kB)

Abstract

This project aims to classify age and gender of a person using Deep Neutral Network as classification method and calculate its accuracy. The author conduct a research using Deep Neural Network classifier to classify a person age and gender. The algorithm will use dataset from caffemodel, that known as a pre trained model, as the classifier source to classify age and gender. The algorithm use face as the object that will classified. This research will use 20 faces as the object of this research to find out its classification result and its accuracy. After the object detected, the face will be processed in the algorithm to be a ready image for classification process. After both of the classification process done, the score will printed on the output for the classification process result. After the research was done, it has been shown that Deep Neural Network has a high percentage of accuracy of classification process in the algorithm that the author used, to be specific, it reach above 90 percent of accuracy for each classification of age and gender.That means Deep Neural Network are one of machine learning methods of classification that is highly recommended to use for other classification purpose.

Item Type:	Thesis (Other)
Subjects:	000 Computer Science, Information and General Works > 004 Data processing & computer science
Divisions:	Faculty of Computer Science > Department of Informatics Engineering
Depositing User:	Mr Yosua Norman Rumondor
Date Deposited:	29 Sep 2023 03:45
Last Modified:	29 Sep 2023 03:45
URI:	http://repository.unika.ac.id/id/eprint/32940

Actions (login required)

View Item