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RWIS based road condition prediction using machine learning algorithms
(2021-06-26)
The need for a forecasting model of road conditions is becoming evermore critical, given the effects of ever-increasing severity in weather. Drastic changes in weather, especially cold fronts, often lead to dangerous roads. ...
Video Outpainting using Conditional Generative Adverarial Networks
(2021)
Recent advancements in machine learning and neural networks have pushed the boundaries of what computers can achieve. Generative adversarial networks are a specific type of neural network that have proved wildly successful ...
Development of Deep Learning Methodologies for Modeling Navigational Features in Continuous Spaces
(2021-12)
This thesis proposes generalized methodologies to model navigational features of continuous spaces using deep learning architectural approaches. Navigational features impact how an entity can effectively travel within a ...
Do We Really Need Deep Learning?: A Study on Play Identification using SEM Images
(2021-05-14)
Deep learning has become an integral part of image classification and segmentation, especially with the use of convolutional neural networks (CNN) and their variants. Although computationally expensive and time-consuming, ...
Assessing the Relation between Mud Components and Rheology for Loss Circulation Prevention Using Polymeric Gels: A Machine Learning Approach
(2021-03-03)
The traditional way to mitigate loss circulation in drilling operations is to use preventative and curative materials. However, it is difficult to quantify the amount of materials from every possible combination to produce ...
Statistical and deep learning methods for geoscience problems
(2021-12-15)
Machine learning is the new frontier for technology development in geosciences and has developed extremely fast in the past decade. With the increased compute power provided by distributed computing and Graphics Processing ...