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 136 for “"Classification problem"”.
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On the Classification Problem for the Control Vector Fields
Made available in DSpace on 2014-12-11T18:24:13Z (GMT). No. of bitstreams: 1 7511751.pdf: 1365102 bytes, checksum: 87d0ba24f8e73360de536a18086b6ebe (MD5) Previous issue date: 1974
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A Deterministic Approach to Partitioning Neural Network Training Data for the Classification Problem
The classification problem in discriminant analysis involves identifying a function that accurately classifies observations as originating from one of two or more mutually exclusive groups. Because no single classification technique works best for all problems, many different techniques have been …
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A Radial Basis Function Approach to a Color Image Classification Problem in a Real Time Industrial Application
… function network approach to solve a color image classification problem in a real time industrial application. Radial basis function networks are employed to classify the images of finished wooden parts in terms of their color and species. Other classification methods are also examined in this …
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The application of neural networks to communication channel equalisation : a comparison between localised and non-localised basis functions
Neural networks have been applied to a number of problems over the past few years. One of the emerging applications of neural networks is adaptive communication channel equalisation. This area of research has become prominent due to the reformulation of the equalisation problem as a classification …
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Linear and ellipsoidal pattern separation: theoretical aspects and experimental analysis
This thesis deals with a pattern classification problem, which geometrically implies data separation in some Euclidean feature space. The task is to infer a classifier (a separating surface) from a set or sequence of observations. This classifier would later be used to discern observations of …
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Exploring social tagging graph for web object classification
We study web object classification problem with the novel exploration of social tags. Automatically classifying web objects into manageable semantic categories has long been a fundamental preprocess for indexing, browsing, searching, and mining these objects. The explosive growth of heterogeneous …
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Machine Learning for Information Extraction
… Each of the tasks is formalized as a learning problem and appropriate learning algorithms are developed and applied to the problem. The dissertation studies part of speech tagging as a multi-class classification problem, and applies the SNOW (Sparse Network of Winnows) learning system to learn …
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A controlled sensing approach to graph classification
… a graph in order to maximize the decay of classification error probability with sample size by formulating the classification problem as a composite sequential hypothesis test with control. In contrast to prior work, posing the problem as a composite sequential hypothesis test with control …
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Predicting Flavonoid UGT Regioselectivity with Graphical Residue Models and Machine Learning.
… challenging and biologically significant protein classification problem: the prediction of flavonoid UGT acceptor regioselectivity from primary protein sequence. Novel indices characterizing graphical models of protein residues are introduced. The indices are compared with existing amino acid …
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Clinical Interpretation of Novel Copy Number Variations
… CNVs as a multiple instance binary classification problem. We analyze the current state of clinical techniques, then present and test several novel statistical approaches to the problem.
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Automatinis užduočių apimties vetinimas naudojant natūralios kalbos apdorojimo įrankius /
… tools solving the task effort estimation problem as accurately as 80%. Research is made to justify this claim, where a classic perceptron based machine learning architecture is compared against newer, transformer-based architectures. In this research, the task effort estimation problem is …
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Exploring the Use of Supervised Machine Learning Algorithms to Classify Simulated Balance Deficits
… accuracies. The long-term goal is to create a classification system that can accurately detect the presence, severity, and progression of balance deficits in individuals who have a somatosensory deficiency. Postural sway data was collected from 27 healthy, young participants that had no …
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3D Deep Learning Segmentation for Fiber Break Analysis of Carbon Fiber Reinforced Polymer Tomograms
… of carbon fiber breaks, an imbalanced classification problem with less than 0.01% of the data being fiber breaks of interest, shows overall similar performance between 2D and 3D segmentation (e.g., IoU scores of 67.5% and 70.7%, respectively). Qualitative and quantitative analysis …
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Classification and discriminant analysis
… review of the literature pertaining to the problem of classification. General concepts and principles of the classification problem are explored. These results are presented especially for populations under a normal distribution. Three major techniques of classification and discriminant …
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Target Detection Using a Wavelet-Based Fractal Scheme
… with the EF feature for a general texture classification problem. The wavelet-based technique yielded a lower classification error than EF, which motivated the comparison between the two techniques presented in this paper. Experimental results show that the proposed techniques feature map …
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An end-to-end grading neural network for middle-school math problems
… grader checks a student's solution to a math problem against the answer key and gives a score. This thesis proposes a deep-learning-powered grader that takes the place of the human grader. The task is formulated as a classification problem. Given an answer key and a student's solution, the …
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