A new comparison framework to survey neural networks‐based vehicle detection and classification approaches

S Hashemi, H Emami… - International Journal of …, 2021 - Wiley Online Library
The vehicle detection and classification (VDC) problem has received much attention recently
due to the increased security threats and the need to develop intelligent transportation …

Intelligent traffic signal automation based on computer vision techniques using deep learning

MT Ubaid, T Saba, HU Draz, A Rehman… - IT …, 2022 - ieeexplore.ieee.org
Traffic congestion in highly populated urban areas is a huge problem these days. A lot of
researchers have proposed many systems to monitor traffic flow and handle congestion …

A novel ensemble learning approach of deep learning techniques to monitor distracted driver behaviour in real time

HU Draz, MZ Khan, MUG Khan… - … and Data Analytics …, 2021 - ieeexplore.ieee.org
Driver distraction causes one of the major problems in road safety and accidents. According
to the World Health Organization (WHO), over 285,000 estimated accidents happened as a …

Crowd Density Identification at Cross Section using machine learning and deep learning

H Dubey, M Singh, R Raj… - 2023 5th International …, 2023 - ieeexplore.ieee.org
The estimation of crowd density at cross sections is a significant problem in the crowd
analysis. In this study, we provide a novel technique for determining crowd density using …

Scene Graph Generation With Structured Aspect of Segmenting the Big Distributed Clusters

AR Khan, H Mukhtar, T Saba, O Riaz, MUG Khan… - IEEE …, 2022 - ieeexplore.ieee.org
Accurate fruit counting is one of the significant phenotypic traits for crucial fruit harvesting
decision making. Existing approaches perform counting through detection or regression …

Toward a framework and sumo-based simulation for smart traffic control using multiagent learning

RMD Golam, N Fukuta - 2021 10th International Congress on …, 2021 - ieeexplore.ieee.org
In this paper, we propose an approach and its frame-work of our adaptive traffic control
system using reinforcement learning. The proposed approach attempts to determine the best …