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- Artificial intelligence (2)
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- Deep neural networks (1)
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- Myocardial revascularization; fluoroscopy angiography; myocardial perfusion imaging; image fusion (1)
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Articles 1 - 4 of 4
Full-Text Articles in Engineering
A Deep Machine Learning Approach For Predicting Freeway Work Zone Delay Using Big Data, Abdullah Shabarek
A Deep Machine Learning Approach For Predicting Freeway Work Zone Delay Using Big Data, Abdullah Shabarek
Dissertations
The introduction of deep learning and big data analytics may significantly elevate the performance of traffic speed prediction. Work zones become one of the most critical factors causing congestion impact, which reduces the mobility as well as traffic safety. A comprehensive literature review on existing work zone delay prediction models (i.e., parametric, simulation and non-parametric models) is conducted in this research. The research shows the limitations of each model. Moreover, most previous modeling approaches did not consider user delay for connected freeways when predicting traffic speed under work zone conditions. This research proposes Deep Artificial Neural Network (Deep ANN) and …
A 3d Image-Guided System To Improve Myocardial Revascularization Decision-Making For Patients With Coronary Artery Disease, Haipeng Tang
A 3d Image-Guided System To Improve Myocardial Revascularization Decision-Making For Patients With Coronary Artery Disease, Haipeng Tang
Dissertations
OBJECTIVES. Coronary artery disease (CAD) is the most common type of heart disease and kills over 360,000 people a year in the United States. Myocardial revascularization (MR) is a standard interventional treatment for patients with stable CAD. Fluoroscopy angiography is real-time anatomical imaging and routinely used to guide MR by visually estimating the percent stenosis of coronary arteries. However, a lot of patients do not benefit from the anatomical information-guided MR without functional testing. Single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) is a widely used functional testing for CAD evaluation but limits to the absence of anatomical information. …
Application Of Artificial Intelligence And Geographic Information System For Developing Automated Walkability Score, Md Mehedi Hasan
Application Of Artificial Intelligence And Geographic Information System For Developing Automated Walkability Score, Md Mehedi Hasan
Dissertations
Walking is considered as one of the major modes of active transportation, which contributes to the livability of cities. It is highly important to ensure walk friendly sidewalks to promote human physical activities along roads. Over the last two decades, different walk scores were estimated in respect to walkability measures by applying different methods and approaches. However, in the era of big data and machine learning revolution, there is still a gap to measure the composite walkability score in an automated way by applying and quantifying the activityfriendliness of walkable streets. In this study, a street-level automated walkability score was …
Efficient Hardware Implementations Of Bio-Inspired Networks, Anakha Vasanthakumaribabu
Efficient Hardware Implementations Of Bio-Inspired Networks, Anakha Vasanthakumaribabu
Dissertations
The human brain, with its massive computational capability and power efficiency in small form factor, continues to inspire the ultimate goal of building machines that can perform tasks without being explicitly programmed. In an effort to mimic the natural information processing paradigms observed in the brain, several neural network generations have been proposed over the years. Among the neural networks inspired by biology, second-generation Artificial or Deep Neural Networks (ANNs/DNNs) use memoryless neuron models and have shown unprecedented success surpassing humans in a wide variety of tasks. Unlike ANNs, third-generation Spiking Neural Networks (SNNs) closely mimic biological neurons by operating …