A survey of deep learning-based image restoration methods for enhancing situational awareness at disaster sites: the cases of rain, snow and haze

S Karavarsamis, I Gkika, V Gkitsas, K Konstantoudakis… - Sensors, 2022 - mdpi.com
This survey article is concerned with the emergence of vision augmentation AI tools for
enhancing the situational awareness of first responders (FRs) in rescue operations. More …

Predicting spatio-temporal traffic flow: a comprehensive end-to-end approach from surveillance cameras

Y Feng, Y Zhao, X Zhang, SFA Batista… - Transportmetrica B …, 2024 - Taylor & Francis
Traffic flow forecasting is an essential aspect of intelligent traffic management. It enables
timely and proactive management of modern transport systems, increasing efficiency and …

Strategies to enhance the level of service and safety of rural roads: A case study

Q Ai, J Zhang, Y Ye - PLoS one, 2024 - journals.plos.org
Faced with the contradiction between the increasing traffic volume and the aging road
infrastructures in the rural area, this paper aims to propose feasible strategies to enhance …

Machine Learning-Driven Calibration of Traffic Models Based on a Real-Time Video Analysis

E Lopukhova, A Abdulnagimov, G Voronkov… - Applied Sciences, 2024 - mdpi.com
Accurate traffic simulation models play a crucial role in developing intelligent transport
systems that offer timely traffic information to users and efficient traffic management …

[HTML][HTML] Efficacy Evaluation of You Only Learn One Representation (YOLOR) Algorithm in Detecting, Tracking, and Counting Vehicular Traffic in Real-World Scenarios …

JA Guzmán-Torres, FJ Domínguez-Mota… - AI, 2024 - mdpi.com
This research explores the efficacy of the YOLOR (You Only Learn One Representation)
algorithm integrated with the Deep Sort algorithm for real-time vehicle detection …

A case study: deployment of real-time smart city monitoring using YOLOv7 in Selangor cyber valley

N Azmi, LM Kamarudin, AS Ali Yeon, A Zakaria… - Journal of Ambient …, 2024 - Springer
This paper focuses on the smart security aspect of smart city initiatives, and specifically on
road traffic monitoring. We describe the design and deployment of smart traffic monitoring in …

Development of Artificial Intelligent-Based Methodology to Prepare Input for Estimating Vehicle Emissions.

E Yavuz, A Öztürk, NGN Balkanlı… - Applied Sciences …, 2024 - search.ebscohost.com
Abstract Featured Application: The methodology employed in this study represents an
innovative approach to the accurate estimation of variable vehicle emissions. Machine …

EasyVis2: A Real Time Multi-view 3D Visualization for Laparoscopic Surgery Training Enhanced by a Deep Neural Network YOLOv8-Pose

YH Sun, G Shen, J Chen, J Fernandes, H Jiang… - arXiv preprint arXiv …, 2024 - arxiv.org
EasyVis2 is a system designed for hands-free, real-time 3D visualization during
laparoscopic surgery. It incorporates a surgical trocar equipped with a set of micro-cameras …

Critical Analysis of Impact of Traffic Parameters in Traffic Count System

S Ramteke, S Sawalapurkar… - … on Emerging Trends …, 2023 - ieeexplore.ieee.org
The Growth in use of vehicles on the road is a matter of worry for management authorities as
it needs a faster and reliable method to manage traffic and its data. The detection of vehicles …

Integrating Machine Learning in Urban Pedagogy: Addressing Homelessness in Skid Row

T Meshkani - Architecture, 2024 - mdpi.com
This paper investigates the application of machine learning in urban and architectural
education, with a focus on addressing homelessness in Skid Row, Los Angeles. It presents …