A review of vision-based traffic semantic understanding in ITSs

J Chen, Q Wang, HH Cheng, W Peng… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
A semantic understanding of road traffic can help people understand road traffic flow
situations and emergencies more accurately and provide a more accurate basis for anomaly …

Toward planet-wide traffic camera calibration

K Vuong, R Tamburo… - Proceedings of the IEEE …, 2024 - openaccess.thecvf.com
Despite the widespread deployment of outdoor cameras, their potential for automated
analysis remains largely untapped due, in part, to calibration challenges. The absence of …

Intellıgent transportatıon system applıcatıons: a traffıc management perspectıve

V Bhatia, V Jaglan, S Kumawat, V Siwach… - … systems: Proceedings of …, 2022 - Springer
The rapid increase in population has increased the traffic density in urban areas. In current
scenario, the major challenges faced by transportation systems are congestion, accidents …

Traffic density estimation and traffic control using convolutional neural network

AK Ikiriwatte, DDR Perera… - … on Advancements in …, 2019 - ieeexplore.ieee.org
The existing traffic light control systems are inefficient due to the usage of predefined
algorithms on offline data. This causes in numerous problems such as long delays and a …

Robust automatic monocular vehicle speed estimation for traffic surveillance

J Revaud, M Humenberger - Proceedings of the IEEE/CVF …, 2021 - openaccess.thecvf.com
Even though CCTV cameras are widely deployed for traffic surveillance and have therefore
the potential of becoming cheap automated sensors for traffic speed analysis, their large …

Estimating traffic density on roads using convolutional neural network with batch normalization

M Hasan, S Das, MNT Akhand - 2021 5th International …, 2021 - ieeexplore.ieee.org
Traffic Jam is one of the major problems of modern urban life. Regardless of the socio-
economic structure of a country, almost all the countries of the world suffer from this problem …

[Retracted] Research on Urban Traffic Industrial Management under Big Data: Taking Traffic Congestion as an Example

Y Zhang, S Yang, H Zhang - Journal of Advanced …, 2022 - Wiley Online Library
This paper establishes a prediction model of traffic flow, where three cycle dependent
components are used to model three characteristics of traffic data, respectively. CNN is used …

Traffic density estimation using transfer learning with pre-trained inceptionresnetv2 network

MNT Akhand, S Das, M Hasan - Machine Intelligence and Data Science …, 2022 - Springer
Traffic jam is a major problem in urban areas. It is a global-scale problem, and almost every
country and every city face this to some extent. Traffic jam is a man-made problem. That …

Traffic density estimation using progressive neural architecture search

V Kumar, J Prasad, B Singh - Journal of Statistics and Management …, 2020 - Taylor & Francis
The current research work is to develop an automated system for estimating the traffic
density of roads at traffic junctions and proposed a traffic control algorithm for smooth …

A novel approach of traffic density estimation using CNNs and computer vision

LAT Nguyen, TX Ha - European Journal of Electrical Engineering and …, 2021 - ejece.org
In modern life, we face many problems, one of which is the increasingly serious traffic jam.
The cause is the large volume of vehicles, inadequate infrastructure and unreasonable …