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 …

[PDF][PDF] Towards Real-time Traffic Flow Estimation using YOLO and SORT from Surveillance Video Footage.

N Algiriyage, R Prasanna, K Stock, E Hudson-Doyle… - ISCRAM, 2021 - researchgate.net
Traffic emergencies and resulting delays cause a significant impact on the economy and
society. Traffic flow estimation is one of the early steps in urban planning and managing …

Utilizing Federated Learning for Enhanced Real-Time Traffic Prediction in Smart Urban Environments.

M Kumari, Z Ulmas, R Suseendra… - International …, 2024 - search.ebscohost.com
Federated Learning (FL), a crucial advancement in smart city technology, combines real-
time traffic predictions with the potential to enhance urban mobility. This paper suggests a …

[引用][C] Multi-source multimodal deep learning to improve situation awareness: an application of emergency traffic management: a thesis presented in partial fulfilment …

RN Hewa Algiriyage - 2023 - Massey University

[引用][C] Band Traffic Light Scheduling for Waiting time Reduction

C Nagarjuna, SS Reddy, UV Prasad, TL Babu…