Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 736 for “"machine learning techniques"”.
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Machine Learning Techniques for Gesture Recognition
… movement is a large field of interest to Human-Machine Interface researchers. The reason for this lies in the large emphasis humans place on gestures while communicating with each other and while interacting with machines. Such gestures can be digitized in a number of ways, including both …
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Enriching Knowledge Graphs Using Machine Learning Techniques
… enriches FEW knowledge graphs using advanced machine learning techniques. Our overarching goal is to improve decision-making, knowledge discovery, and provide improved search results for data scientists in the FEW domains. Given an input knowledge graph (constructed on raw FEW datasets), …
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Predicting an Economic Recession Using Machine Learning Techniques
… to improve economic recession prediction using machine learning (ML) techniques by developing an inch-perfect and efficient prediction model in order to avoid greater government deficits, growing inequality, significantly decreased income, and higher unemployment. The study objective was to …
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Machine Learning Techniques for Augmenting Hematological Malignancy Diagnosis
This dissertation examines the use of modern machine learning (ML) methods to enhance the diagnostic workflow of hematological malignancies, particularly in cytogenetics and clinical flow cytometry. The recent advancements in the field of ML provide a unique opportunity to develop, adapt, and …
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Machine learning techniques for identifying railroad ballast degradation
… degradation using a combination of advanced machine vision and machine learning techniques. Initially, various computer vision algorithms are used to generate features associated with images of ballast cross sections at different degradation levels. Next, the generated features are used …
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Machine Learning Techniques for Code Generation and Optimization
We follow a similar approach and use a classifier learning system to generate high performance libraries for matrix-matrix multiplication. Our library generator produces matrix multiplication routines that use recursive layouts and several levels of tiling. Our approach is to use a classifier …
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Reconstructing Textual File Fragments Using Unsupervised Machine Learning Techniques
… analysis motivated by a desire to demonstrate machine learning's applicability to Digital Forensics. Using a categorized corpus of Usenet, Bulletin Board Systems, and other assorted documents a series of experiments are conducted using machine learning techniques to train classifiers which are …
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Applying Supervised Machine Learning Techniques to Municipal Bond Trading
… we will examine how artificial intelligence or machine learning can be used to make better municipal bond trading decisions. The paper will examine a variety of classification models trained in a supervised environment. The paper will discuss: i. How to prepare data for machine learning analysis …
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Leveraging Machine Learning Techniques in Power and Transportation Systems
… authenticity. Fortunately, the surge of modern machine learning techniques has enabled us to grapple with seemingly impossible to solve problems, to overcome the computational complexity, and mine the knowledge to guide the operational tasks, especially in complex cyber physical systems such as …
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Predicting outpatient appointment non-attendances using machine learning techniques
… is mainly focused on traditional statistical techniques that fail to capture the complex relationships in this type of data. This thesis uses machine learning approaches to investigate whether these factors are consistent across a range of medical specialties. A predictive model based on …
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Development of flood prediction models using machine learning techniques
… methodologies have not kept pace with modern machine learning. To leverage these algorithms, new models must be developed to efficiently capture the relationships among the variables that influence these events in a given region. These models can be used by emergency management personnel to …
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Vision-based human action recognition using machine learning techniques
… The most popular and prominent state-of-the-art techniques are reviewed, evaluated, compared, and presented. Based on the literature review, these techniques are categorized into handcrafted feature-based and deep learning-based approaches. The proposed action recognition framework is then based …
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Supervised Machine Learning Techniques for Short-Term Load Forecasting
… for energy management based on the demand. Machine Learning Algorithms has been in the forefront for prediction algorithms. This Thesis is mainly aimed to provide utility companies with a better insight about the wide range of Techniques available to forecast the load demands based on …
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Applying machine learning techniques to an imperfect information game
… limit Hold‟em). This allows simple reinforcement learning techniques to be used which previously not been considered for the game of multi-player hold‟em. A related hidden Markov model was designed to be fitted to records of poker play without using any private information. Belief vectors …
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Digging Deep Into Urban Mobility Data Through Machine Learning Techniques
L'abstract è presente nell'allegato / the abstract is in the attachment
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Bridging the gap: Applying machine learning techniques in digital forensics
… technologies across various industries, virtual machines (VMs) offer cost-effective solutions for obtaining computing power without the burden of initial investment or ongoing maintenance. However, the widespread use of VMs also increases the risk of malicious actors attempting to gain …
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Real time detection of malicious webpages using machine learning techniques
… at to detect harmful webpages, by running the machine learning models on a remote website. The problem with this approach is that the detection rate is slow, because of the need to handle large number of webpages. There is a gap in knowledge to research into which machine learning algorithms …
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Learning with less: machine learning techniques for scarce medical data
Deep learning has demonstrated significant potential in medical applications. However, its success often depends on large, clean datasets, a condition rarely met in real-world medical settings, where data is often scarce, incomplete, or expensive. This affects medical machine learning throughout …
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Short tandem repeat (STR) profile authentication via machine learning techniques
… can be created using standard laboratory techniques such as whole genome amplification and molecular cloning. Such technologies can be used to synthesize any STR profile without the need for a physical sample, only knowledge of the desired genetic sequence. Therefore, to preserve the …
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