Department of Mathematics and Computer Science, Summit University, Offa, Nigeria
Review Article
Developing Analytic Frameworks for Real-Time Vehicle Classification and Traffic Analysis Utilizing YOLOv5 and Deep SORT Algorithms
Author(s): M.O. Alimi*, J.A. Benya and R.D. Azeez
Real-time vehicle classification and traffic analysis are critical components of modern intelligent transportation systems. Existing methods often struggle with accuracy and real-time processing requirements. This paper presents a novel approach utilizing the You Only Look Once (YOLOv5) algorithm for vehicle detection and the deep Simple Online and Real-time Tracking (SORT) algorithm for vehicle tracking. The integration of these algorithms offers an innovative solution for accurate and efficient traffic analysis. Experimental results demonstrate the superior performance of the proposed method in comparison to traditional approaches, highlighting its potential for deployment in smart city applications... View More»
DOI:
10.35248/IJIRSET.25.6(1).001
