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 106 for “"classification algorithm"”.
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A vehicle classification algorithm based on telematics data
In the thesis, I develop an algorithm to identify the vehicle model from telematics data. By extracting the features from the accelerometer and GPS data, we obtain the classification features, which then goes through a multiclass random forest classifier. We apply this results into problems of …
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A Probabilistic Classification Algorithm With Soft Classification Output
… a shared memory parallel version of the hybrid classification algorithm IGSCR (iterative guided spectral class rejection), a novel data reduction technique that can be used in conjunction with PIGSCR (parallel IGSCR), a noise removal method based on the maximum noise fraction (MNF), and a …
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The Search for a Cost Matrix to Solve Rare-Class Biological Problems
The rare-class data classification problem is a common one. It occurs when, in a dataset, the class of interest is far outweighed by other classes, thus making it difficult to classify using typical classification algorithms. These types of problems are found quite often in biological datasets, …
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Development of a Support-Vector-Machine-based Supervised Learning Algorithm for Land Cover Classification Using Polarimetric SAR Imagery
Land cover classification using Synthetic Aperture Radar (SAR) data has been a topic of great interest in recent literature. Food commodities output prediction through crop identification, environmental monitoring, and forest regrowth tracking are some of the many problems that can be aided by land …
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An anomaly detection model utilizing attributes of low powered networks, IEEE 802.15.4e/TSCH and machine learning methods
… size, noise influence, model aging process and classification algorithm are investigated against performance accuracy using data collected from an operational wireless network, comprising more than one hundred nodes, during a six-month period. An important attribute of this work is that the …
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Implementation and evaluation of a bony structure suppression software tool for chest X-ray imaging
… tool and analyse its effects on a texture-based classification algorithm in order to assist in the analysis of chest X-ray images. The diagnosis of pulmonary tuberculosis (TB) often includes the evaluation of chest X-ray images, and the reliability of image interpretation depends upon the …
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Classification of finger gestures from myoelectric signals
… I describe and compare three methods for static classification of EMG signals. I then go on to explore methods for adapting the classifiers over time and for sequential analysis of the gesture stream by combining the static classification algorithm with a hidden Markov model. I conclude with an …
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Brief Study of Classification Algorithms in Machine Learning
… of three most commonly used Machine Learning algorithms: k-Nearest Neighbors (kNN), Decision Trees and Naïve Bayes. All these algorithms fall under the Classification algorithm category of Unsupervised Machine Learning. This paper is constructed structurally in explaining the working theory …
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Development and Evaluation of Approaches for Quantitative Optical Molecular Imaging of Neoplasia
… glucose analog, 2-NBDG, in 9 patient samples. A classification algorithm using quantitative image features resulted in an area under the curve (AUC) of 0.83, though the main advantage of this technique may be to understand spatial heterogeneity of biomarker expression and how this correlates with …
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Improving Network Performance Through Endpoint Diagnosis And Multipath Communications
… is identified as network related additional algorithms are triggered to detect the device responsible. To achieve the first step, we revisit the question: how much can you infer about a failure using TCP statistics collected at one of the endpoints in a connection? Using an agent that …
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A context-sensitive meta-classifier for color-naming
… to colors. This is especially challenging for algorithms which attempt to replicate human categorization for communicative tasks. Additionally, mismatched color models between dialog partners can lead to a back-and-forth negotiation of terms to find common ground. This thesis presents a …
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A generalized hierarchical approach for data labeling
… this thesis was to develop a data type agnostic classification algorithm best suited for problems where there are a large number of similar labels (e.g., classifying a port versus a shipyard). The most common approach to this issue is to simply ignore it, and attempt to fit a classifier against …
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Combining phrase-based and tree-to-tree translation
… machine translation, using a feature-based classification algorithm. Instead of just using language models, translation models, or internal confidence scores, we sought out other features that could be used to determine which of two translations to select. We combined the outputs from a …
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A framework for smart traffic management using heterogeneous data sources
… The social media component consists of a text classification algorithm to identify traffic related tweets. These traffic messages are then geolocated using Natural Language Processing (NLP) techniques. Finally, with the purpose of further analysing user emotions within the tweet, stress and …
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Using Phoneme Groups to Train Deep Learning Models to Remove Reverberation in Cochlear Implant Stimulus Patterns
… requires knowledge of the anechoic signal, an algorithm must be developed to estimate the mask based on information available in the reverberant signal. Modern algorithms typically use traditional machine learning algorithms or deep learning algorithms to estimate the mask. However, existing …
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Efficiently Learning Monotone Decision Trees with ID3
… effort in designing computationally efficient algorithms for learning Boolean functions from random examples drawn from a uniform distribution. In this paper, I take the ID3 information-gain-first classification algorithm and apply it to the task of learning monotone Boolean functions from …
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Improving Golf Putt Performance with Statistical Learning of EEG Signals
… coherence, which are used as features for the classification algorithm. To predict golfers' performance, the support vector machine algorithm is used to classify the EEG patterns into two categories corresponding to successful and non-successful putts. The proposed approach utilizes a large …
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Design of a low power VLSI systems powered by ambient mechanical vibration
… that implements a power scalable detection and classification algorithm for a biomedical sensor. This chip demonstrates appropriate architectural and circuit techniques for low to medium throughput sensor applications. It consumes 550 n W at 1.5 V with a 1 kHz clock frequency.
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Analyzing and Classifying Neural Dynamics from Intracranial Electroencephalography Signals in Brain-Computer Interface Applications
… feature extractors, feature selectors, and classification algorithms. In this work, we explore the different classification algorithms currently used in electroencephalographic (EEG) signal classification and assess their performance on intracranial EEG (iEEG) data. We first discuss the …
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