Browsing by Subject "machine learning"

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  • Analyzing 50 kHz rats’ vocalizations using machine learning approaches 
    Yazdani Sangdeh, Shayan; University of Lethbridge. Faculty of Arts and Science (Lethbridge, Alta. : University of Lethbridge, Dept. of NeuroscienceArts and ScienceDepartment of Neuroscience, 2021)
    Recent studies propose different categorization schemes for rats’ 50 kHz vocalizations. This study attempted to differentiate these categories based on spectrographic features extracted manually and using convolutional ...
  • Classification of computer programming contest programs based on gender, region and software metrics 
    Zinnat, Sara Binte; University of Lethbridge. Faculty of Arts and Science (Lethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer ScienceArts and ScienceDepartment of Mathematics and Computer Science, 2021)
    This research focuses on determining the effect of sociolinguistics characteristics (particularly, gender and region) on computer programs. Previous studies have demonstrated the use of machine learning techniques to analyze ...
  • Combining state-of-the-art models for multi-document summarization using maximal marginal relevance 
    Adams, David; University of Lethbridge. Faculty of Arts and Science (Lethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer ScienceArts and ScienceDepartment of Mathematics and Computer Science, 2021)
    In Natural Language Processing, multi-document summarization (MDS) poses many challenges to researchers. While advancements in deep learning approaches have led to the development of several advanced language models capable ...
  • Computer program categorization with machine learning 
    Rafee, Md Mahmudul Hasan; University of Lethbridge. Faculty of Arts and Science (Lethbridge, Alta. : Universtiy of Lethbridge, Department of Mathematics and Computer ScienceArts and ScienceDepartment of Mathematics and Computer Science, 2017)
    Machine learning techniques have been applied to improve the learning process and to learn about the utilization of natural languages. Previous research has shown that similar techniques can be applied in the analysis ...
  • Detection of sleep and wake substates through unsupervised machine learning in rat hippocampus and primary motor cortex LFP recordings 
    Balogun, Pauline; University of Lethbridge. Faculty of Arts and Science (Lethbridge, Alta. : Universtiy of Lethbridge, Department of NeuroscienceArts and ScienceDepartment of Neuroscience, 2019)
    This project investigated whether unsupervised machine learning could detect differences in global or local microstates across different rodent brain, in the effects of procedural learning, and clustering validity indices ...
  • Do sociolinguistic variations exist In programming? 
    Naz, Fariha; University of Lethbridge. Faculty of Arts and Science (Lethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer ScienceArts and ScienceDepartment of Mathematics and Computer Science, 2015)
    Machine learning techniques are currently widely used in the analysis of natural language. This thesis focuses on extending these techniques for analysis of programming languages. In particular we are interested in determining ...
  • Transformer-based multi-hop question generation 
    Emerson, John Robert; University of Lethbridge. Faculty of Arts and Science (Lethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer ScienceArts and ScienceDepartment of Mathematics and Computer Science, 2022)
    Question generation is the parallel task of question answering, where given an input context and, optionally, an answer, the goal is to generate a relevant and fluent natural language question. Although recent works on ...
  • An unsupervised classification-based time series change detection approach for mapping forest disturbance 
    Parshakov, Ilia; University of Lethbridge. Faculty of Arts and Science (Lethbridge, Alta. : University of Lethbridge, Dept. of Geography and EnvironmentArts and ScienceDepartment of Geography and Environment, 2021)
    Unsupervised Classification to Change (UC-Change) is a new remote sensing approach for mapping areas affected by logging and wildfires. It addresses the main limitations of existing image time-series change detection ...
  • Verifying tag annotation and performing genre classification in music data via association analysis 
    Arjannikov, Tom (Lethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer ScienceArts and ScienceDepartment of Mathematics and Computer Science, 2014)
    Music Information Retrieval aims to automate the access to large-volume music data, including browsing, retrieval, storage, etc. The work presented in this thesis tackles two non-trivial problems in the field. First ...