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Object Recognition Using Convolutional Neural Network Architecture

FYP 2 SEM 2 2019/2020

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Main Author: Prasantth a/l Subramaniam
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Language:English
Published: 2023
Subjects:
tensorflow
deep learning
age gender classification
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spelling my.uniten.dspace-212172023-05-04T13:09:16Z Object Recognition Using Convolutional Neural Network Architecture Prasantth a/l Subramaniam tensorflow deep learning age gender classification FYP 2 SEM 2 2019/2020 Evolution of current modern era demands a fast and excellent way of computing day by day. It has dramatically transformed how we work and live. Involvement of Artificial Intelligence (AI) has significantly show the intelligent behavior side of today’s computers. Now machines are making intelligent decisions in recognizing objects, people, and languages. In has massively create an impact in a world driven by technology. My thesis illustrates the method of recognizing age and gender of a human in real time with the help of pre-trained deep learning models. In my project work, the age database has a total of 13,420 face images which has been separated into two different class; child and adult. The gender database has a total of 2,000 face images which has been separated into two different class; male and female. The main idea of this research is to study the performance of deep learning models by training the architectures consist of neural networks to classify images based on class and can be use in real time classification as well. The three best deep learning models which are VGG16, ResNet50 and MobileNet been selected based on their performance on training and validation accuracy. Hence, some classification on test images to witness the performance of the neural networks. My project work to be illustrated in this thesis. 2023-05-03T16:15:45Z 2023-05-03T16:15:45Z 2020-02 https://irepository.uniten.edu.my/handle/123456789/21217 en application/pdf
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
topic tensorflow
deep learning
age gender classification
spellingShingle tensorflow
deep learning
age gender classification
Prasantth a/l Subramaniam
Object Recognition Using Convolutional Neural Network Architecture
description FYP 2 SEM 2 2019/2020
format
author Prasantth a/l Subramaniam
author_facet Prasantth a/l Subramaniam
author_sort Prasantth a/l Subramaniam
title Object Recognition Using Convolutional Neural Network Architecture
title_short Object Recognition Using Convolutional Neural Network Architecture
title_full Object Recognition Using Convolutional Neural Network Architecture
title_fullStr Object Recognition Using Convolutional Neural Network Architecture
title_full_unstemmed Object Recognition Using Convolutional Neural Network Architecture
title_sort object recognition using convolutional neural network architecture
publishDate 2023
_version_ 1806423419989786624
score 13.222552

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