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 214 for “"Thresholding"”.
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Wavelet Thresholding for Non (Necessarily) Gaussian Noise
… is obtained and the performance of wavelet thresholding for <br>median filtered data is investigated. <br>The subject of chapter 5 is an extension of Stein's unbiased risk estimation <br>for general classes of infinitely divisible noise in the location model. <br>Stein's unbiased risk …
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Improved thresholding and quantization techniques for image compression
… Therefore, to overcome this problem, an improved thresholding and quantization techniques for image compression is proposed. Firstly, the generated wavelet coefficients obtained from the Discrete Wavelet Transform (DWT) process are thresholded by the proposed Standard Deviation-Based Wavelet …
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Denoising by wavelet thresholding using multivariate minimum distance partial density estimation
… of sparsity. We develop an adaptive wavelet thresholding algorithm that addresses each of these issues. We model the wavelet coefficients with a two-component mixture in which the noise component is Gaussian but the signal component need not be specified. We use a new technique in density …
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Sensitivity to Distributional Assumptions in Estimation of the ODP Thresholding Function
Recent technological advances in fields like medicine and genomics have produced high-dimensional data sets and a challenge to correctly interpret experimental results. The Optimal Discovery Procedure (ODP) (Storey 2005) builds on the framework of Neyman-Pearson hypothesis testing to optimally test …
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THRESHOLDING METHODS FOR LESION SEGMENTATION OF BASAL CELL CARCINOMA IN DERMOSCOPY IMAGES
… that have been applied to BCCs. Fifteen auto-thresholding techniques were implemented for BCC lesion segmentation; but, only five were selected for use in algorithm development. A novel technique was developed to automatically expand BCC lesion borders, to completely circumscribe the lesion. …
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Inertial iterative thresholding with applications to sparse and low-rank signal recovery
… class of methods known collectively as iterative thresholding algorithms. These methods have been used by researchers for several decades to solve various optimization problems that arise in signal processing, inverse problems, pattern recognition and other related fields. One such problem of …
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MICON: Connection logic circuits using current-based data representation and thresholding methods
CONLOG (for connection logic) is the name given to a set of fast current controlled circuits characterized by its methods of data representation and gate interconnections. Because of its properties, only one basic circuit topology is required to implement a particular CONLOG family. Furthermore, to …
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Relaxations of the optimality requirement on the thresholding greedy algorithm for bases of Banach spaces
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms
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Tenko: A Zero Trust Inspired Framework for Real-Time Network Defense via Intelligent Thresholding and Node-Level Anomaly Scoring
As our digital world becomes more connected, detecting unusual or harmful behavior on networks is more important than ever. Traditional systems that monitor for cyber threats often rely on fixed rules or need labeled examples of attacks, which makes them less effective in real-world, fast-changing …
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The effect of thresholding a maximum likelihood classifier on the accuracy of a landsat classification of a forested wetland
Although the maximum likelihood classifier is a popular classification technique, there is an inherent problem associated with the 100% classification of a scene. This is because there will inevitably be pixels within a study area that have a low probability of belonging to any of the predefined …
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COMPRESSIVE SENSING BASED IMAGE RECONSTRUCTION FOR COMPUTED TOMOGRAPHY DOSE REDUCTION
… L1 regularization. We derive several analytic thresholding representations for Lp (0≤p≤1) regularization and develop a corresponding general thresholding algorithm which is adequate and efficient for large-scale problems such as CT reconstruction. The analytic thresholding representation for …
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Design of optoelectronic activation, local memory and weighting circuits for Compact Integrated Optoelectronic Neural (COIN) Co-processor
… thesis, we design and implement optoelectronic thresholding (activation), weighting and memory circuits for the COIN processor. The first version involved the design of fixed thresholding and weighting functions. The second version incorporated a local capacitive memory element as well as …
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Anthropomorphic Model for Medical Image Quality Assessment
… candidate selection and decision-making. Thresholding during the candidate selection stage dynamically refines regions of interest, while stage-specific feature usage in the decision-making stage optimizes diagnostic accuracy. These innovations allow the model to align more closely with …
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Applications of wavelet transforms in pattern recognition and de-noising
… algorithm. Instead of using univariate thresholding developed by Donoho, we adopt bivariate thresholding as pioneered by Downie and Silverman. Numerical simulation shows that TI multiwavelet de-noising is better than TI single wavelet de-noising when soft thresholding is used.
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Optimization Techniques for Multi-object Detection and Tracking on Live-cell Fluorescence Microscopy Images and Their Applications
… annotations, leading to reliance on adaptive thresholding. Current adaptive thresholding approaches have two significant limitations: Firstly, they cannot handle the heteroscedasticity of image data well and result in biased outputs. Secondly, they deal with frames of time-series imaging data …
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Tissue segmentation using medical image processing chain optimization
… of entropy, similarity, clustering, contour, or thresholding. These specially developed functions target specific feature or step in the presented segmentation algorithms. To the best of our knowledge, this thesis is the first research work that uses an optimizer to build and optimize parameters …
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In silico modelling to advance arterial spin labelling magnetic resonance imaging
… as signals from non-capillary blood. Intensity thresholding is one approach that has been proposed for minimising the noncapillary blood signal within an ASL MR image. This technique involves eliminating voxels with signal intensity above a set threshold as these encompass large vessels feeding …
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Patch-based Denoising Algorithms for Single and Multi-view Images
… image denoising. An adaptive collaborative thresholding filter is proposed which consists of a classification map and a set of various thresholding levels and operators. These are exploited when the collaborative hard-thresholding step is applied. Moreover, the collaborative Wiener filtering …
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Image enhancement techniques applied to solar feature detection
… The initial preprocessing step involves local thresholding to convert grayscale images into black-and-white pictures with chromosphere granularity enhanced. An alternative preprocessing method, based on image normalization and global thresholding is presented. The next step employs …
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