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Smart city article details

Title	An Android Application For Unwanted Vehicle Detection And Counting
ID_Doc	7536
Authors	Khalid M.; Ashraf A.; Bangyal W.H.; Iqbal M.
Year	2023
Published	Proceedings - 2023 Human-Centered Cognitive Systems, HCCS 2023
DOI	http://dx.doi.org/10.1109/HCCS59561.2023.10452502
Abstract	The significance of vehicle identification and monitoring is increasing in the field of traffic management. The Intelligent Transportation System (ITS) is a highly efficient way to address the issue of traffic congestion in metropolitan areas and is a prominent focus in the development of smart cities. One specific application is the monitoring and forecasting of fluid flow. The suggested system aims to implement automated vehicle identification and recognition processing utilizing static image datasets. Significant progress in vehicle detection technology has been made due to the emergence of unmanned driving and intelligent transportation research. The suggested system utilizes the deep learning technique to investigate the vehicle detection algorithm, specifically employing the fundamental phase target detection algorithm known as the YOLO algorithm. Hence, the initial approach involves the manipulation of visual data from a publicly available collection of road vehicles for the purpose of training. A vehicle detection model is developed using the YOLO algorithm to demonstrate the detection performance separately. The suggested system's contribution is in the enhancement of the conventional YOLO network's architecture, enabling precise identification of vehicle targets. © 2023 IEEE.
Author Keywords	Android; Machine Learning; Vehicle Detection; Yolo

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