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.
Results
Showing 1 to 20 of 27 for “"denoise"”.
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Laboratory characterization of seismicty and development of a deep learning framework to denoise seismic data in the field
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2024-12-01
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Computing and Comprehending Topology: Persistence and Hierarchical Morse Complexes
… enables us to simplify a space topologically. To denoise two-dimensional density functions, we first construct Morse complexes over their underlying space. Applying persistence, we create a hierarchy of progressively coarser Morse complexes. The thesis describes implementations of the algorithms …
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Burst Imaging with Learned Continuous Kernels
… sample location information to demosaic, denoise and merge the burst into a high quality output.
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Temporally consistent FastDVDNet: an overlap loss implementation for FastDVDNet
… is a model with fast inference time, or time to denoise a frame, and reduced flickering. The solution will primarily cover the modification of FastDVDNet’s high-level architecture and loss function. Additionally, the problem space of video denoising and methods of determining a model’s …
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Sparse and Redundant Image Representations Using Adaptive Dictionaries in Digital Image Denoising
… redundant dictionaries and has been shown to denoise images fairly well. We look to improve this method by adapting the dictionaries to more accurately represent specific image features. The image features were chosen to be the details, textures, and smooth regions of the image. Two different …
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Towards high-resolution magnetic resonance spectroscopic imaging: spatiotemporal denoising and echo-time selection
… denoising approach. We then further propose to denoise MRSI data by exploiting low-rank properties. These are two low-rank structures of MRSI data, one due to partial separability and the other due to linear predictability of MRSI data. Denoising is performed by arranging the measured data in …
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Cryo-electron microscopy image analysis using multi-frequency vector diffusion maps
… addition, we propose a graph filtering scheme to denoise the images using the eigenvalues and eigenvectors of the MFVDM matrices. Through both simulated and publicly available real data, we demonstrate that our proposed method is efficient and robust to noise compared with the state-of-the-art …
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Online parameter selection for source separation using non-negative matrix factorization
… how to use blind source separation algorithms to denoise audio mixtures containing speech and various background noises. We mainly focus on how to imple- ment an online source separation algorithm which can handle non-stationary noises. To address the implementation, we also present a study on how …
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Neural Network Learning for Time-Series Predictions Using Constrained Formulations
… lag period when a low-pass filter is employed to denoise the band. The new constraints enable active training in the lag period that greatly improves the prediction accuracy in the lag period. Extensive prediction experiments on financial time series have been conducted to exploit the modeling …
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Computational methods to dissect the genetic basis of human disease
… a machine learning framework to impute and denoise Mendelian disease-derived pathogenicity scores. I assess the informativeness of Mendelian pathogenicity scores for common disease and improve upon existing scores. In the third chapter, I prioritize disease-critical cell types by integrating …
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3D sensing and mapping using mobile color and depth sensors
… and correct for these distortions and use the denoised measurements for various applications in vision related fields. In particular, we tackle the following problems: First, we propose a novel algorithm that takes in few depth images and utilizes them to simultaneously denoise and calibrate …
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Acoustic source localization
… Most of these applications are able to denoise Gaussian noise from the surrounding, but have trouble removing impulse like noises. One source of impulse-like noise is the snapping shrimps. The acoustic signals they emit from snapping their claws hinder technologies, but can also be used …
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Machine learning for understanding protein sequence and structure
… the noise generation process and accurately denoise micrographs, improving the ability of experamentalists to examine and interpret their data. We then introduce a neural network model for understanding continuous variability in proteins in cryoEM data by explicitly disentangling variation of …
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Online Denoising Solutions for Forecasting Applications
… the second category, multiple discrete universal denoisers are developed that can be used for the online denoising of discrete value time series. In the third category, we develop a noisy channel reversal model based on the similarities between time series forecasting and data communication and …
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New Models and Analysis Techniques for Diagnostic Fracture Injection Tests
… methodology is proposed to effectively denoise the test data and analyze fracture injection tests. Unlike conventional techniques, this methodology does not rely on assumptions regarding fracture geometry and rock properties. Additionally, it takes into account the impact of heat …
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Understanding the Limits of Lithium-Air Batteries – NMR and Thermodynamic Studies
… that Gaussian processes can also be used to denoise NMR data, matching or outperforming current denoising methods in many cases. Finally, a potential additive to the electrolyte, lithium iodide, is discussed. Lithium iodide had previously been proposed to reduce the charge overpotential and …
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An image processing decisional system for the Achilles tendon using ultrasound images
… a complete system which enables one to crop, denoise, enhance, extract the important features and classify AT ultrasound images. The proposed application focuses on developing an automated system platform. Generally, systems for analysing ultrasound images involve four stages, pre-processing, …
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Topic Model-based Mass Spectrometric Data Analysis in Cancer Biomarker Discovery Studies
… composing the heterogeneous data. Additionally, denoise deconvolution model (DMM) is proposed to capture the noise signals in samples based on purified profiles. Variational expectation-maximization (VEM) and Markov chain Monte Carlo (MCMC) methods are used to draw inference on the latent …
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A near-optimal wavelet-based estimation technique for video sequences
This thesis presents a method for estimation of a video signal given a data set with Poisson noise. The cameras used in creating video sequences are often charge-coupled devices, which produce data by way of a counting process, leading to noise with a Poisson distribution. Because many applications …
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Machine Learning and Bayesian Statistics for Seismic Compressive Sensing
… data, learn features from training data, denoise and create uncertainty maps for predictions in seismic surveys.
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