Volume 2 - Issue 2, March - April 2026

Traffic congestion has become a major problem in modern urban areas due to rapid growth in vehicle population. Traditional traffic monitoring methods, such as manual counting and sensor-based systems, are often inefficient, costly, and unable to provide real-time analysis. This paper proposes a Traffic Tracker Using Deep Learning Algorithm** that automatically detects and tracks vehicles from video surveillance footage. The system utilizes a convolutional neural network (CNN) for accurate vehicle detection and employs a tracking algorithm to maintain vehicle identities across frames.

Vinisha.J, Mr.I. Gobi,"Traffic Tracker Using Deep Learning Algorithm" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(2): Page(814-817) Mar-Apr 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.