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Physical Sciences and Mathematics Commons

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Full-Text Articles in Physical Sciences and Mathematics

Robot Learning From Human Observation Using Deep Neural Networks, Michael Elachkar Feb 2022

Robot Learning From Human Observation Using Deep Neural Networks, Michael Elachkar

Electronic Theses and Dissertations

Industrial robots have gained traction in the last twenty years and have become an integral component in any sector empowering automation. Specifically, the automotive industry implements a wide range of industrial robots in a multitude of assembly lines worldwide. These robots perform tasks with the utmost level of repeatability and incomparable speed. It is that speed and consistency that has always made the robotic task an upgrade over the same task completed by a human. The cost savings is a great return on investment causing corporations to automate and deploy robotic solutions wherever feasible.

The cost to commission and set …


Enhancing Multi-View 3d-Reconstruction Using Multi-Frame Super Resolution, Michael Lee Jan 2022

Enhancing Multi-View 3d-Reconstruction Using Multi-Frame Super Resolution, Michael Lee

Electronic Theses and Dissertations

Multi-view stereo is a popular method for 3D-reconstruction. Super resolution is a technique used to produce high resolution output from low resolution input. Since the quality of 3D-reconstruction is directly dependent on the input, a simple path is to improve the resolution of the input.

In this dissertation, we explore the idea of using super resolution to improve 3D-reconstruction at the input stage of the multi-view stereo framework. In particular, we show that multi-view stereo when combined with multi-frame super resolution produces a more accurate 3D-reconstruction.

The proposed method utilizes images with sub-pixel camera movements to produce high resolution output. …


Approaches For Eye-Tracking While Reading, Xiaohao Sun Oct 2021

Approaches For Eye-Tracking While Reading, Xiaohao Sun

Electronic Theses and Dissertations

In this thesis, we developed an algorithm to detect the correct line being read by participants. The comparisons of the reading line classification algorithms are demonstrated using eye-tracking data collected from a realistic reading experiment in front of a low-cost desktop-mounted eye-tracker. With the development of eye-tracking techniques, research begins to aim at trying to understand information from the eyes. However, state of the art in eye-tracking applications is affected by a large amount of measurement noise. Even the expensive eye-trackers still suffer significant noise. In addition, the inherent characteristics of gaze movement increase the difficulty of obtaining valuable information …