Vehicle Tracking System

dc.contributor.authorRao Mubashar Ali , Ali Suhaib Shahid , Ammar Yasee
dc.contributor.authorFA17-BCS-124 , FA17-BCS-082 , FA17-BCS-033
dc.contributor.authorDr. Zeeshan Gillani
dc.contributor.authorLHR TP 7519
dc.date.accessioned2026-02-25T04:50:43Z
dc.date.issued2021
dc.description.abstractThe increase in population in metropolitan cities has given rise to severe traffic management problems and security issues. The rise in CCTV (Closed-circuit television) based solution has enabled us to monitor traffic but the sheer number of the cameras has given rise to another challenge of monitoring these systems and analyse this rich information. The advancement in computer vision techniques and GPU (Graphical processing unit) has now enable techniques than can automatically task which was only possible by humans in the past. CNN (Convolutional neural networks) based models can enable us to use real time videos of traffic data to aid in analysing the traffic conditions which in turn helps us in effective decision making regarding our cities to make them intelligent and safe. We will employ futuristic algorithms on the NVIDIA AI city datasets to evaluate the traffic detection and tracking systems.
dc.identifier.urihttps://repository.cuilahore.edu.pk/handle/123456789/2189
dc.language.isoen
dc.publisherLibrary Information Services, COMSATS University Islamabad, Lahore Campus
dc.relation.ispartofseriesLHR TP 7519
dc.subjectTECHNOLOGY::Information technology::Computer science
dc.subjectDr. Zeeshan Gillani
dc.titleVehicle Tracking System
dc.typeThesis

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