Assessing traffic surveillance data is a prevalent utilization of deep learning methodologies.
Video processing techniques were employed to develop the system aimed at determining …

The majority of fatalities, injuries, and property damage are caused by traffic collisions. The
principal cause of death is frequent excessive speeding. Deep learning techniques are now …

This paper proposes an intelligent traffic surveillance system that detects the vehicle and its
speed, colour, direction, and type of vehicle using computer vision and deep learning. This …

The density of vehicles on roads has increased manifold over the last few decades. A
seamless system to detect and track a particular vehicle can solve many problems, like traffic …

This project focuses on real-time congestion detection and tracking to improve traffic safety
by enabling mechanisms to improve drivers' situational awareness. With real-time …

The idea behind this research idea is to develop a deep learning model for traffic vehicle
detection, which predicts types of vehicles (Truck, Car, Bike) using frame difference through …

Intelligent transportation systems (ITS) are the integration of information and
communications technologies with applications which are significant in traffic control and …

Moving objects detection, type recognition, and traffic analysis in videobased surveillance
systems is an active area of research which has many applications in road traffic monitoring …

The unpredictability and blockage of current transportation frameworks frequently produce
traffic circumstances that endanger the security of the individuals and it can cause several …

The classification and tracking of vehicles is a crucial component of modern transportation
infrastructure. Transport authorities make significant investments in it since it is one of the …