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 14 of 14 for “"Feature Classification"”.
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Spectral feature classification of oceanographic processes using an autonomous underwater vehicle
… performance. As a case study, AUV-based classification is applied to distinguish ocean convection from internal waves. The mingled spectrum templates are derived from the MIT Ocean Convection Model and the Garrett-Munk internal wave spectrum model. To allow for mismatch between modeled …
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Spectral feature classification of oceanographic processes using an autonomous underwater vehicle
… performance. As a case study, AUV-based classification is applied to distinguish ocean convection from internal waves. The mingled spectrum templates are derived from the MIT Ocean Convection Model and the Garrett-Munk internal wave spectrum model. To allow for mismatch between modeled …
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SARLBP and STMO-GA : two novel description and selection approaches for challenging feature classification problems
Texture analysis and classification is a much-researched area due to its significance within computer vision and pattern recognition applications. Broadly speaking, two approaches for texture classification are found in the literature today: Classical and Deep Learning (DL) based. Typical Deep …
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OpenIR [Open Infrared] : enhancing environmental monitoring through accessible remote sensing, in Indonesia and beyond
… as ondemand map layers, automates environmental feature classification, experiments with flood risk mapping, and interfaces IR data with crowd- and citizen-maps. OpenIR's initial use case is emergency management and environmental monitoring in the economically developing and ecologically …
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Applications of Computational Geometry and Computer Vision
… locating and automatically classifying facial features from images. State of the art methods for facial feature classification are compared and new methods for finding empty hyper-rectangles are introduced. The problem of finding holes is then linked to the problem of extracting features from …
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A machine vision-based approach to measuring the size distribution of rocks on a conveyor belt
… are most likely to be rock edges based on rock features. Finally, rock recognition using feature classification is applied to remove non-rock watershed boundaries. The projected rock area distribution of a test-set is measured and compared to corresponding projected areas of manually segmented …
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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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UNDERSTANDING DIFFERENTIAL ABUNDANCE IN MICROBIAL ECOLOGY USING COMMUNITY STRUCTURE.
… statistical methods for identifying microbial features that are associated with macroscopic states. Differentially abundant microbial features can broaden the understanding of disease mechanisms and guide prevention, diagnosis, prognosis, and therapy, yet current DAA methods often yield …
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Context-Based classification of objects in topographic data
… topographic databases model real world features as vector data objects. These can be point, line or area features. Each of these map objects is assigned to a descriptive class; for example, an area feature might be classed as a building, a garden or a road. Topographic data is subject to …
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Fault Identification of UPFC-Compensated Transmission Lines in Complex Microgrids Using an Intelligent Relaying Scheme Based on Discrete Wavelet Transform and ANN Classifier
… study uses discrete wavelet transform (DWT) for feature extraction and artificial neuron network (ANN) for feature classification of fault currents. The main objectives are automatic detection and identification of fault type with the best accuracy, reliability, and reduced computational …
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A Wavelet-Based Rail Surface Defect Prediction and Detection Algorithm
… while the other uses the Wavelet Transform for feature extraction. Both of these algorithms use an artificial neural network for feature classification. The third algorithm uses the Wavelet Transform to perform a regularity analysis on the signal. The algorithms are validated with the collected …
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Face Verification with Veridical and Caricatured Images using Prominent Attributes
Caricatures, with their exaggerated features, offer a surprisingly efficient means for individuals to recognize each other compared to veridical (real) images. However, it is still a difficult task in machine learning to match veridical images to caricatures. This is due to the poor quality of …
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Beyond LiDAR for Unmanned Aerial Event-Based Localization in GPS Denied Environments
… in the field of data-driven detection and classification approaches typically rely on computationally expensive inputs such as image or video-based methods [6, 91]. However, the information given by an acoustic signal offers several advantages, such as low computational needs and possible …
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Towards a Fast and Accurate Face Recognition System from Deep Representations
… components of a machine perception algorithm are feature extraction followed by classification or regression. The features representing the input data should have the following desirable properties: 1) they should contain the discriminative information required for accurate classification, 2) they …