Browsing by Thesis Advisor "Adu-Gyamfi, Yaw"
Now showing items 1-6 of 6
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Artificial intelligence enabled automatic traffic monitoring system
(University of Missouri--Columbia, 2019)The rapid advancement in the field of machine learning and high-performance computing have highly augmented the scope of video-based traffic monitoring systems. In this study, an automatic traffic monitoring system is ... -
Automated conflation framework for integrating transportation big datasets
(University of Missouri--Columbia, 2019)The constant merging of the data, commonly known as Conflation, from various sources, has been a vital part for any phase of development, be it planning, governing the existing system or to study the effects of any ... -
Detection and quantification of delamination in concrete via time-lapse thermography with machine learning
(University of Missouri--Columbia, 2021)This study developed a framework to automatically extract sub-surface defects from time-lapse thermography (TLT) images of reinforced concrete bridge components. Traditional approaches for processing TLT data typically ... -
TITAN : an interactive, web-based platform for transportation, data integration, and analytics
(University of Missouri--Columbia, 2020)State transportation agencies regularly collect and store various types of data for different uses such as planning, traffic operations, design, and construction. These large datasets contain treasure troves of information ... -
TMA (track mounted attenuators) involved work zones safety analysis and modeling, using machine learning to predict crash severity and crash frequency in the state of Missouri
(University of Missouri--Columbia, 2018)When talking about road maintenance safety, it is an unavoidable talking about the TMA usage, as it located in the work zone intended to reduce the damage while crash happened and at the same time protect the related ... -
TMA (Truck Mounted Attenuators) alert system-development and testing
(University of Missouri--Columbia, 2022)Truck Mounted Attenuators (TMAs) play a crucial role in safety of work zones as they decrease the impact of the crashes, reduce fatalities and injuries, and increase safety. However, there are almost no solid solutions to ...