Advances and trends in real time visual crowd analysis
Real time crowd analysis represents an active area of research within the computer vision
community in general and scene analysis in particular. Over the last 10 years, various …
community in general and scene analysis in particular. Over the last 10 years, various …
Internet of things enabled convolutional neural networks: applications, techniques, challenges, and prospects
The Internet of Things (IoT) has been proven useful for the interconnection of computing
devices embedded in objects to enable objects to send and receive data through the …
devices embedded in objects to enable objects to send and receive data through the …
Pictorial depiction on controlling crowd in smart conurbations using Internet of Things with switching algorithms
The proliferation of smart conurbations entails an efficient system design for managing all
the crowds in public places. Multitude controlling procedures are carried out for controlling …
the crowds in public places. Multitude controlling procedures are carried out for controlling …
Label noise robust crowd counting with loss filtering factor
Z Xu, H Lin, Y Chen, Y Li - Applied Artificial Intelligence, 2024 - Taylor & Francis
Crowd counting, a crucial computer vision task, aims at estimating the number of individuals
in various environments. Each person in crowd counting datasets is typically annotated by a …
in various environments. Each person in crowd counting datasets is typically annotated by a …
Convolutional neural network for human crowd analysis: a review
This research paper presents a review of the use of convolutional neural networks (CNNs)
for human crowd analysis. The paper discusses the challenges and limitations of methods …
for human crowd analysis. The paper discusses the challenges and limitations of methods …
Drone Based Fire Detection System Based on Convolutional Neural Network
Open fires are happening more and more throughout Malaysia. It is either intentional or
accidental fire. The most dangerous is an accidental fire because it may not be detected by …
accidental fire. The most dangerous is an accidental fire because it may not be detected by …
[HTML][HTML] Analyzing Crowd Behavior in Highly Dense Crowd Videos Using 3D ConvNet and Multi-SVM
Crowd behavior presents significant challenges due to intricate interactions. This research
proposes an approach that combines the power of 3D Convolutional Neural Networks …
proposes an approach that combines the power of 3D Convolutional Neural Networks …
A survey: Crowds detection method on public transportation
DA Leone, H Novianto, R Setiawan… - … Science and Artificial …, 2021 - ieeexplore.ieee.org
Face recognition is a computer technology being used in a variety of applications that
identifies human faces in digital images. At this time, face recognition can be used to find out …
identifies human faces in digital images. At this time, face recognition can be used to find out …
Collaborative services for Crowd Safety systems across the Edge-Cloud Computing Continuum
Crowd or mass gatherings at various venues such as entertainment events or transportation
systems are faced by individuals on a daily basis. Crowd management for large-scale …
systems are faced by individuals on a daily basis. Crowd management for large-scale …
[PDF][PDF] Classification and Identification of Internet of Things Networks Data using Deep Learning.
OP Ene - Journal of Software Engineering and Applications, 2024 - researchgate.net
The Internet of Things (IoT) has revolutionized the way devices and objects communicate
and interact, generating vast amounts of data. Efficiently classifying and identifying IoT …
and interact, generating vast amounts of data. Efficiently classifying and identifying IoT …