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Defense: Gaussian Process Modeling for Upsampling Algorithms with Applications in Computer Vision and Computational Fluid Dynamics

Speaker Name: 
Steven Reeves
Speaker Title: 
PhD Candidate
Start Time: 
Friday, March 20, 2020 - 10:00am
End Time: 
Friday, March 20, 2020 - 11:00am
Via Zoom Presentation

Abstract: Across a variety of fields, interpolation algorithms have been used to upsample low resolution or coarse data fields. In this work, novel Gaussian Process based methods are employed to solve a variety of upsampling problems. Specifically three applications are explored: coarse data prolongation in Adaptive Mesh Refinement (AMR) in the field of Computational Fluid Dynamics, accurate document image upsampling to enhance Optical Character Recognition (OCR) accuracy, and fast and accurate Single Image Super Resolution (SISR). For AMR, a new, efficient, and “3rd order accurate” algorithm called GP-AMR is presented. Next, a novel, non-zero mean, windowed GP model is generated to upsample low resolution document images to generate a higher OCR accuracy, when compared to the industry standard. Finally, a hybrid GP convolutional neural network algorithm is used to generate a computationally efficient and high quality SISR model. 

Event Type: 
Dongwook Lee
Graduate Program: 
Applied Mathematics PhD