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 “"Data Segmentation"”.
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Machine learning and coresets for automated real-time data segmentation and summarization
In this thesis, we develop a family of real-time data reduction algorithms for large data streams, by computing a compact and meaningful representation of the data called a coreset. This representation can then be used to enable efficient analysis such as segmentation, summarization, …
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Cardiac MRI Data Segmentation Using the Partial Differential Equation of Allen–Cahn Type
The work deals with segmentation of image data using the algo- rithm based on numerical solution of the geometrical evolution partial differen- tial equation of the Allen-Cahn type. This equation has origin in the description of motion by mean curvature and has diffusive character. The diffusion …
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SnapshotNet: Self-supervised Feature Learning for Point Cloud Data Segmentation Using Minimal Labeled Data
<p>Manually annotating complex scene point cloud datasets is both costly and error-prone. To reduce the reliance on labeled data, a new model called SnapshotNet is proposed as a self-supervised feature learning approach, which directly works on the unlabeled point cloud data of a complex 3D scene. …
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Discrete-time band-limited extrapolation algorithms for radar imaging systems
… Iterative Weighted-Norm, Control-Point, Data Segmentation, and Cascade Form algorithms. Each modifies the reconstruction subspace used in the extrapolation. The basic extrapolation algorithms are the first three which form the foundation of this thesis. The Data Segmentation algorithm …
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Supervised manifold distance segmentation
… a simple and robust method for image and volume data segmentation based on manifold distance metrics. In this approach, pixels in an image are not considered as points with color values arranged in a grid. In this way, a new data set is built by a transform function from one traditional 2D image …
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Design and evaluation of a data-dependent low-power 8x8 DCT/IDCT
… complexities regardless of the input. Recently, data-dependent signal processing has been applied to the DCT/IDCT. These algorithms have variable run-time complexities. A new two-dimensional 8 x 8 low-power DCT/IDCT design is implemented using VHDL by applying the data-dependent signal-processing …
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Melt Detection and Estimation in Greenland Using Tandem QuikSCAT and SeaWinds Scatterometers
… (SIR) algorithm and a new temporal data segmentation technique. Melt detection is performed using a layered electromagnetic model combined with a Markov chain model. The new melt detection method allows classification of the snow-pack into three states: melt, refreeze, and frozen. …
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Passive object recognition using intrinsic shape signatures
… recognition possible. These modules were 1) a data segmentation module, 2) an object recognition module using Intrinsic Shape Signature[10] (ISS) to find feature points in our LiDAR data, and 3) various visualization modules to ensure that each module was behaving properly.
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Morphometric Otolith Analysis
… age, performing tests over three 2-class otolith datasets across six discrete and concurrent age groups. Impact of segmentation methods are assessed to determine whether automated or expert segmented methods of boundary extraction are more advantageous, and whether constructed classi�ers can be …
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Inferring Complex Activities for Context-aware Systems within Smart Environments
… to knowledge by developing a semantic-enabled data segmentation approach with user-preferences. The second study takes the segmented set of sensor data to investigate and recognise human ADLs at multi-granular action level; coarse- and fine-grained action level. At the coarse-grained actions …
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Development of a statistical shape and appearance model of the skull from a South African population
… planning, finite element analysis, model-based segmentation, and in the fields of anthropometry and forensics. Similar applications can make use of SSMs and SAMs of the skull. A combination of the SSM and SAM of the skull can also be used in model-based segmentation. This document presents the …
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Non-invasive Assessment of Swallowing and Phonation using High-density Electromyography
… and human error in handling large high-density datasets. Development of the framework involved optimising filtering and windowing, alongside a comprehensive comparison of four algorithms for detecting low-quality channels. Among these, a density-based local anomaly detection method performed …
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High-Dimensional Inference with Heterogeneous Data
Modern large-scale data offers the exciting prospect of advancing our understanding of many scientific phenomena, but also presents significant computational and statistical challenges for traditional inference methods. A core assumption that underpins much of statistical theory and modelling is …
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Innovative AI-Enabled Digital Twins for Smart Battery Management: Enhancing Battery Life and Performance in Smart Vehicles
L'abstract è presente nell'allegato / the abstract is in the attachment