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Novel Statistical Modeling Methods For Traffic Video Analysis, Hang Shi
Novel Statistical Modeling Methods For Traffic Video Analysis, Hang Shi
Dissertations
Video analysis is an active and rapidly expanding research area in computer vision and artificial intelligence due to its broad applications in modern society. Many methods have been proposed to analyze the videos, but many challenging factors remain untackled. In this dissertation, four statistical modeling methods are proposed to address some challenging traffic video analysis problems under adverse illumination and weather conditions.
First, a new foreground detection method is presented to detect the foreground objects in videos. A novel Global Foreground Modeling (GFM) method, which estimates a global probability density function for the foreground and applies the Bayes decision rule …
Toward Self-Reconfigurable Parametric Systems: Reinforcement Learning Approach, Ting-Yu Mu
Toward Self-Reconfigurable Parametric Systems: Reinforcement Learning Approach, Ting-Yu Mu
Dissertations
For the ongoing advancement of the fields of Information Technology (IT) and Computer Science, machine learning-based approaches are utilized in different ways in order to solve the problems that belong to the Nondeterministic Polynomial time (NP)-hard complexity class or to approximate the problems if there is no known efficient way to find a solution. Problems that determine the proper set of reconfigurable parameters of parametric systems to obtain the near optimal performance are typically classified as NP-hard problems with no efficient mathematical models to obtain the best solutions. This body of work aims to advance the knowledge of machine learning …
A Holistic Computational Approach To Boosting The Performance Of Protein Search Engines, Majdi Ahmad Mosa Maabreh
A Holistic Computational Approach To Boosting The Performance Of Protein Search Engines, Majdi Ahmad Mosa Maabreh
Dissertations
Despite availability of several proteins search engines, due to the increasing amounts of MS/MS data and database sizes, more efficient data analysis and reduction methods are important. Improving accuracy and performance of protein identification is a main goal in the community of proteomic research. In this research, a holistic solution for improvement in search performance is developed.
Most current search engines apply the SEQUEST style of searching protein databases to define MS/MS spectra. SEQUEST involves three main phases: (i) Indexing the protein databases, (ii) Matching and Ranking the MS/MS spectra and (iii) Filtering the matches and reporting the final proteins. …