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 97 for “"Supervised classification"”.
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Supervised Classification of Imbalanced Bidding Fraud Data
… are not identified. Our goal is to devise a SB classification model, which is able to efficiently differentiate between legitimate bidders and shill bidders. For this thesis, we employ a real SB training dataset, which is unlabeled. First, we label the SB dataset by the help of hierarchical …
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Supervised Classification Using Copula and Mixture Copula
<p>Statistical classification is a field of study that has developed significantly after 1960's. This research has a vast area of applications. For example, pattern recognition has been proposed for automatic character recognition, medical diagnostic and most recently in data mining. Classical …
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Projection methods for clustering and semi-supervised classification
… methods for the purposes of clustering and semi-supervised classification, with a primary focus on clustering. A number of contributions are presented which address this problem in a principled manner; using projection pursuit formulations to identify subspaces which contain useful information …
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Supervised classification and network location problems via mathematical optimization
… addresses several problems in the fields of Supervised Classification and Location Theory using tools and techniques coming from Mathematical Optimization. A brief description of these problems and the methodologies proposed for their analysis and resolution is given below. In the first …
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Observing the Seasonal Evolution of Supraglacial Ponds in High Mountain Asia: A Supervised Classification Approach
… applicable in the HMA region. An unsupervised k-means classifier is used to train a supervised Random Forest Classifier (RFC) in the Google Earth Engine platform. This study adapts algorithms used by Dell et al., (2021) for application in the HMA region. The classifier is trained on …
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Semi-supervised classification of social media posts : identifying sex-industry posts to enable better support for those experiencing sex-trafficking
Social media is both helpful and harmful to the work against sex trafficking. On one hand, social workers carefully use social media to support individuals experiencing sex trafficking. On the other hand, traffickers use social media to groom and recruit individuals into trafficking situations. …
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The information regularization framework for semi-supervised learning
In recent years, the study of classification shifted to algorithms for training the classifier from data that may be missing the class label. While traditional supervised classifiers already have the ability to cope with some incomplete data, the new type of classifiers do not view unlabeled data …
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Seafloor habitat characterization, classification, and maps for the lower Piscataqua River estuary
… were used to implement segmentations and classifications of the seafloor, and measurements from underwater images and physical samples were used to relate segmentations and predictions to observed seafloor characteristics. Texture analysis, using local Fourier histogram (LFH) texture …
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Enabling Proactive Quality in Commercial Airplanes using Natural Language Processing
… of such quality data. We investigate both an unsupervised clustering method and a supervised classification method to group these reports by the broader "quality topic" they pertain to, using semantic relationship-maintaining text "embeddings" as features. We find success in supervised …
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Land cover mapping through optimizing remote sensing data for SVM classification
Support Vector Machines (SVMs) are a new supervised classification technique that has its roots in statistical learning theory. It has gained popularity in fields such as machine vision, artificial intelligence, digital image processing and more recently remote sensing. The three commonly used SVMs …
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Smart Data Analytics for Manufacturing Processes
… data analytics approaches for the objectives of supervised classification and fault detection, as they arise for example in the context of process monitoring schemes for chemical manufacturing processes. For both objectives, a visual representation of the method selection process is presented in …
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Land Cover of Virginia From Landsat Thematic Mapper Imagery
… computers. Hypercluster aggregation, an unsupervised classification method, was used when hazy and mountainous conditions were not present. A haze correction procedure by Lavreau (1991) was used, followed by a supervised classification on coastal areas. An enhanced supervised …
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Spectral Identification of Wild Rice (Zizania palustris L.) Using Indigenous Knowledge and Landsat Multispectral Data
… utilized to build training data polygons for a supervised classification. By testing several supervised classification algorithms, it was hypothesized that wild rice could be delineated from other aquatic vegetation, but the coarse (30 m X 30 m) spatial resolution of Landat-7 ETM+ multispectral …
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Spectral Identification of Wild Rice (Zizania palustris L.) Using Indigenous Knowledge and Landsat Multispectral Data
… utilized to build training data polygons for a supervised classification. By testing several supervised classification algorithms, it was hypothesized that wild rice could be delineated from other aquatic vegetation, but the coarse (30 m X 30 m) spatial resolution of Landat-7 ETM+ multispectral …
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Learning With An Insufficient Supply Of Data Via Knowledge Transfer And Sharing
… from other sources and new methods (both supervised and un-supervised) have to be developed to selectively share and transfer knowledge. In this dissertation, we present both supervised and un-supervised techniques to tackle a problem where learning algorithms cannot generalize and require …
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Estimating farm dam storage using SPOT imagery
… resources. SPOT XS imagery and object-oriented classification was used to identify farm dams and their surface area. Two equations applied to determining the capacity of dams were used to convert surface area to volume. The results showed a similarity between fieldwork and object-oriented …
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Development of a Predictive Habitat Evaluation Model for Gaillardia Aestivalis (Walt.) Rock. Var. Winkleri (Cory) Turner Using GPS, Remote Sensing and GIS Techniques
… factor in affecting distribution of the plant. Supervised classification of Landsat TM Image for vegetation classes produced satisfactory results as shown by error matrix. Spatial analysis of coverages were then used to produce potential habitat maps, classified either as favorable or …
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Performance analysis of automatic techniques for tissue classification in magnetic resonance images of the human brain
Classification of Magnetic Resonance (MR) images of the human brain into anatomically meaningful tissue labels is an important processing step in many research and clinical studies in neurology. The medical imaging research community is presented with a wide choice of classification algorithms from …
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Vision-based terrain classification and classifier fusion for planetary exploration rovers
… Here a study of multi-sensor terrain classification for planetary rovers in Mars and Mars-like environments is presented. Supervised classification algorithms for color, texture, and range features are presented based on mixture of Gaussians modeling. Two techniques for merging the …
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