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McKelvey School of Engineering Theses & Dissertations

Theses/Dissertations

2018

Machine learning

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Learning About Large Scale Image Search: Lessons From Global Scale Hotel Recognition To Fight Sex Trafficking, Abby Stylianou Dec 2018

Learning About Large Scale Image Search: Lessons From Global Scale Hotel Recognition To Fight Sex Trafficking, Abby Stylianou

McKelvey School of Engineering Theses & Dissertations

Hotel recognition is a sub-domain of scene recognition that involves determining what hotel is seen in a photograph taken in a hotel. The hotel recognition task is a challenging computer vision task due to the properties of hotel rooms, including low visual similarity between rooms in the same hotel and high visual similarity between rooms in different hotels, particularly those from the same chain. Building accurate approaches for hotel recognition is important to investigations of human trafficking. Images of human trafficking victims are often shared by traffickers among criminal networks and posted in online advertisements. These images are often taken …


Decoding Complexity In Metabolic Networks Using Integrated Mechanistic And Machine Learning Approaches, Tolutola Timothy Oyetunde Dec 2018

Decoding Complexity In Metabolic Networks Using Integrated Mechanistic And Machine Learning Approaches, Tolutola Timothy Oyetunde

McKelvey School of Engineering Theses & Dissertations

How can we get living cells to do what we want? What do they actually ‘want’? What ‘rules’ do they observe? How can we better understand and manipulate them? Answers to fundamental research questions like these are critical to overcoming bottlenecks in metabolic engineering and optimizing heterologous pathways for synthetic biology applications. Unfortunately, biological systems are too complex to be completely described by physicochemical modeling alone.

In this research, I developed and applied integrated mechanistic and data-driven frameworks to help uncover the mysteries of cellular regulation and control. These tools provide a computational framework for seeking answers to pertinent biological …