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Fall 2024

Huo, Dong

Computer vision tasks have seen breakthroughs in recent years thanks to the emergence of deep learning (DL). However, there exists different types of domain-shift problems that may impact the performance of DL-based methods. In low-level vision tasks, \eg, image restoration, the degradation of...

Spring 2018

Fan, Juehui

We present a new algorithm to estimate depth of real-world scenes containing an object semi-submerged in water using a light field camera. Existing hand-held consumer light field cameras are well-suited for automated refocusing, depth detection in outdoor environment. However, when it comes to...

Fall 2024

Kushol, Rafsanjany

Deep learning (DL) has become a leading subset of machine learning (ML) and has been successfully employed in diverse areas, ranging from natural language processing to medical image analysis. In medical imaging, researchers have progressively turned towards multi-center neuroimaging studies to...

Fall 2021

Hang, Zicun

This thesis addresses the problem of super-resolution of environment matting of transparent objects. In contrast to traditional methods of environment matting of transparent objects, which often require a large number of input images or complex camera setups, recent approaches using convolutional...

Fall 2024

Lim, Sangwon

While recent advancements in deep-learning point cloud upsampling methods have improved the input to intelligent transportation systems, they still suffer from issues of domain dependency between synthetic and real-scanned point clouds. This thesis addresses the above issues by proposing a new...

Spring 2016

Hojjati, Saeed

For years, panoramic image stitching has been an interesting problem for re- searchers. Several advances have been made in stitching images that are ac- quired outside of water, but the problem has been poorly explored for under- water images. Image stitching for underwater images can be used in...