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Vehicle Make And TypeClassification Using Keras Deep Neural Network

In this era of globalization, sensors are no longer limited to physical sensors. The development of new technologies enables artificial intelligence (AI) to also function as a higher accuracy sensor. Many countries are currently facing sudden development in their non-rural areas. This situation has...

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Main Author: Sorfina Jasmin Binti Mohtar
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Language:English
Published: 2023
Subjects:
Vehicle
Keras
Deep Neural Network
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id my.uniten.dspace-20568
record_format dspace
spelling my.uniten.dspace-205682023-05-04T18:12:46Z Vehicle Make And TypeClassification Using Keras Deep Neural Network Sorfina Jasmin Binti Mohtar Vehicle Keras Deep Neural Network In this era of globalization, sensors are no longer limited to physical sensors. The development of new technologies enables artificial intelligence (AI) to also function as a higher accuracy sensor. Many countries are currently facing sudden development in their non-rural areas. This situation has lead to the demand for the public safety system to be upgraded and the traffic conditions to be improvised. This project provides a solution in smart traffic monitoring, by classifying the make and type of Malaysian vehicles and non-Malaysian vehicles with an accuracy rate of at least 80%. The project implements Keras architecture with Tensorflow backend applied in Python programming, in the execution of Convolutional Neural Network (CNN). The output of this project highlights the different make and type of vehicles and can be implemented with both image and video input. 2023-05-03T15:06:02Z 2023-05-03T15:06:02Z 2019-10 https://irepository.uniten.edu.my/handle/123456789/20568 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 Vehicle
Keras
Deep Neural Network
spellingShingle Vehicle
Keras
Deep Neural Network
Sorfina Jasmin Binti Mohtar
Vehicle Make And TypeClassification Using Keras Deep Neural Network
description In this era of globalization, sensors are no longer limited to physical sensors. The development of new technologies enables artificial intelligence (AI) to also function as a higher accuracy sensor. Many countries are currently facing sudden development in their non-rural areas. This situation has lead to the demand for the public safety system to be upgraded and the traffic conditions to be improvised. This project provides a solution in smart traffic monitoring, by classifying the make and type of Malaysian vehicles and non-Malaysian vehicles with an accuracy rate of at least 80%. The project implements Keras architecture with Tensorflow backend applied in Python programming, in the execution of Convolutional Neural Network (CNN). The output of this project highlights the different make and type of vehicles and can be implemented with both image and video input.
format
author Sorfina Jasmin Binti Mohtar
author_facet Sorfina Jasmin Binti Mohtar
author_sort Sorfina Jasmin Binti Mohtar
title Vehicle Make And TypeClassification Using Keras Deep Neural Network
title_short Vehicle Make And TypeClassification Using Keras Deep Neural Network
title_full Vehicle Make And TypeClassification Using Keras Deep Neural Network
title_fullStr Vehicle Make And TypeClassification Using Keras Deep Neural Network
title_full_unstemmed Vehicle Make And TypeClassification Using Keras Deep Neural Network
title_sort vehicle make and typeclassification using keras deep neural network
publishDate 2023
_version_ 1806425853528113152
score 13.214268

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