Urban traffic flow analysis based on deep learning car detection from CCTV image series

MV Peppa, D Bell, T Komar… - … Archives of the …, 2018 - isprs-archives.copernicus.org
Traffic flow analysis is fundamental for urban planning and management of road traffic
infrastructure. Automatic number plate recognition (ANPR) systems are conventional …

Traffic density investigation & road accident analysis in India using deep learning

C Manchanda, R Rathi… - … international conference on …, 2019 - ieeexplore.ieee.org
Traffic congestion is a common affair in the big cities and towns. This issue is the outcome of
the rapid increase in the population and increasing number of vehicles, so predicting the …

Vehicular traffic flow prediction using deployed traffic counters in a city

A Almeida, S Brás, I Oliveira, S Sargento - Future Generation Computer …, 2022 - Elsevier
The sustainable growth of cities created the need for better informed decisions based on
information and communication technologies to sense the city and quantify its pulse. An …

Estimating vehicle and pedestrian activity from town and city traffic cameras

L Chen, I Grimstead, D Bell, J Karanka, L Dimond… - Sensors, 2021 - mdpi.com
Traffic cameras are a widely available source of open data that offer tremendous value to
public authorities by providing real-time statistics to understand and monitor the activity …

Real-time traffic analysis using deep learning techniques and UAV based video

H Zhang, M Liptrott, N Bessis… - 2019 16th IEEE …, 2019 - ieeexplore.ieee.org
In urban environments there are daily issues of traffic congestion which city authorities need
to address. Realtime analysis of traffic flow information is crucial for efficiently managing …

Vehicle count system based on time interval image capture method and deep learning mask R-CNN

TT Le, K Aying, FK Pama, I Tabale - TENCON 2019-2019 IEEE …, 2019 - ieeexplore.ieee.org
Traffic congestion is an undesirable problem for big cities especially in third world countries.
Better policy planning and decision-making from the authority comes from well-conducted …

EnsembleNet: A hybrid approach for vehicle detection and estimation of traffic density based on faster R-CNN and YOLO models

U Mittal, P Chawla, R Tiwari - Neural Computing and Applications, 2023 - Springer
Due to static traffic management regulations on roadways, traffic flow may become
congested as it has been growing on roads. Estimating traffic density impacts intelligent …

An analytical framework for accurate traffic flow parameter calculation from UAV aerial videos

I Brkić, M Miler, M Ševrović, D Medak - Remote sensing, 2020 - mdpi.com
Unmanned Aerial Vehicles (UAVs) represent easy, affordable, and simple solutions for
many tasks, including the collection of traffic data. The main aim of this study is to propose a …

Traffic congestion detection from camera images using deep convolution neural networks

P Chakraborty, YO Adu-Gyamfi… - Transportation …, 2018 - journals.sagepub.com
Recent improvements in machine vision algorithms have led to closed-circuit television
(CCTV) cameras emerging as an important data source for determining of the state of traffic …

A deep learning approach for traffic incident detection in urban networks

L Zhu, F Guo, R Krishnan… - 2018 21st international …, 2018 - ieeexplore.ieee.org
Incident detection function is vital for traffic control and management and is an important
prerequisite for quick restoration of smooth traffic flow in urban networks. With accurate and …