Traffic Vehicle Detection of Dhaka City  using Deep Learning Algorithm

Sadat, Md Atiq Aziz; Islam, Md Touhidul; Noman, Abu

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dc.contributor.author	Sadat, Md Atiq Aziz
dc.contributor.author	Islam, Md Touhidul
dc.contributor.author	Noman, Abu
dc.date.accessioned	2025-03-05T05:00:49Z
dc.date.available	2025-03-05T05:00:49Z
dc.date.issued	2024-07-07
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dc.identifier.uri	http://hdl.handle.net/123456789/2349
dc.description	Supervised by Ms. Sanjida Ali, Department of Electrical and Electronic Engineering (EEE) Islamic University of Technology (IUT) Board Bazar, Gazipur, Bangladesh This thesis is submitted in partial fulfillment of the requirement for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2024	en_US
dc.description.abstract	The fast urbanization of Dhaka City has resulted in substantial traffic congestion, requiring effective management techniques. This study investigates the use of deep learning methods, namely convolutional neural networks (CNN), to detect automobiles in traffic in Dhaka. The CNN is trained using photos collected from several places throughout the city. The model is specifically designed to provide optimal performance in detecting objects in real-time, effectively overcoming the difficulties presented by the city's high population density and varied traffic conditions. Preprocessing techniques like picture augmentation and normalization improve the model's ability to handle different scenarios, and its performance is assessed using precision, recall, and F1-score measures. The results demonstrate that the deep learning model outperforms conventional methods in terms of both accuracy and speed, implying significant enhancements for traffic monitoring and management. This study highlights the capacity of deep learning in addressing urban traffic issues, hence facilitating the development of sophisticated intelligent transportation systems in Dhaka.	en_US
dc.language.iso	en	en_US
dc.publisher	Department of Electrical and Elecrtonics Engineering(EEE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh	en_US
dc.subject	Dhaka, Traffic, YOLO, CNN, Deep Learning	en_US
dc.title	Traffic Vehicle Detection of Dhaka City using Deep Learning Algorithm	en_US
dc.type	Thesis	en_US