Vehicle classification in intelligent transport systems: An overview, methods and software perspective
A Gholamhosseinian, J Seitz - IEEE Open Journal of Intelligent …, 2021 - ieeexplore.ieee.org
Vehicle Classification (VC) is a key element of Intelligent Transportation Systems (ITS).
Diverse ranges of ITS applications like security systems, surveillance frameworks, fleet …
Diverse ranges of ITS applications like security systems, surveillance frameworks, fleet …
[PDF][PDF] Traffic surveillance: A review of vision based vehicle detection, recognition and tracking
K Abdulrahim, RA Salam - Int. J. Appl. Eng. Res, 2016 - researchgate.net
Video-based analysis of traffic surveillance is an active area of research, which has a wide
variety of applications in intelligent transport systems (ITSs). In particular, urban …
variety of applications in intelligent transport systems (ITSs). In particular, urban …
EnsembleNet: A hybrid approach for vehicle detection and estimation of traffic density based on faster R-CNN and YOLO models
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 …
congested as it has been growing on roads. Estimating traffic density impacts intelligent …
SINet: A scale-insensitive convolutional neural network for fast vehicle detection
Vision-based vehicle detection approaches achieve incredible success in recent years with
the development of deep convolutional neural network (CNN). However, existing CNN …
the development of deep convolutional neural network (CNN). However, existing CNN …
Intelligent traffic monitoring systems for vehicle classification: A survey
M Won - IEEE Access, 2020 - ieeexplore.ieee.org
A traffic monitoring system is an integral part of Intelligent Transportation Systems (ITS). It is
one of the critical transportation infrastructures that transportation agencies invest a huge …
one of the critical transportation infrastructures that transportation agencies invest a huge …
Fcn-rlstm: Deep spatio-temporal neural networks for vehicle counting in city cameras
In this paper, we develop deep spatio-temporal neural networks to sequentially count
vehicles from low quality videos captured by city cameras (citycams). Citycam videos have …
vehicles from low quality videos captured by city cameras (citycams). Citycam videos have …
Understanding traffic density from large-scale web camera data
Understanding traffic density from large-scale web camera (webcam) videos is a
challenging problem because such videos have low spatial and temporal resolution, high …
challenging problem because such videos have low spatial and temporal resolution, high …
Development of Algorithms for an IoT‐Based Smart Agriculture Monitoring System
Sensor‐based agriculture monitoring systems have limited outcomes on the detection or
counting of vegetables from agriculture fields due to the utilization of either conventional …
counting of vegetables from agriculture fields due to the utilization of either conventional …
Urban traffic density estimation based on ultrahigh-resolution UAV video and deep neural network
This paper presents an advanced urban traffic density estimation solution using the latest
deep learning techniques to intelligently process ultrahigh-resolution traffic videos taken …
deep learning techniques to intelligently process ultrahigh-resolution traffic videos taken …
Automatic detection of bike-riders without helmet using surveillance videos in real-time
In this paper, we propose an approach for automatic detection of bike-riders without helmet
using surveillance videos in real time. The proposed approach first detects bike riders from …
using surveillance videos in real time. The proposed approach first detects bike riders from …