[PDF] Top 20 Multiresolution Gaussian mixture models : theory and applications
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Multiresolution Gaussian mixture models : theory and applications
... The left image, , shows the re onstru tion using only spatial information, using a `soft' de ision: ea h pixel is treated as a mixture, with weights given by the relative magnitudes of [r] ... See full document
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A NOTE ON DISCRETE FRAMES OF TRANSLATES IN CN
... and Li,S., (1998), The theory of multiresolution analysis frames and applications to filter banks, Appl.. and Kutyniok,G., (2012), Finite Frames: Theory and Applications, Birkh¨ a user.[r] ... See full document
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Estimation of a 3D motion field from a multi camera array using a multiresolution Gaussian mixture model
... Abstract. The problem of modelling geometry for video based render- ing has been much studied in recent years, due to the growing interest in ‘free viewpoint’ video and similar applications. Common approaches fall ... See full document
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Bayesian Mixture Models with Applications in Macroeconomics
... a Gaussian distributed error inappropriate in many macroeconomic ...regression models: the uniform prior and the ex- ponential prior [Jacquier et ...error models with alternative prior specifications ... See full document
115
The Sup-norm Perturbation of HOSVD and Low Rank Tensor Denoising
... learning applications such as the exact clustering in high dimensional Gaussian mixture models and the exact support recovery in sub-tensor ... See full document
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Enhanced load profiling for residential network customers
... Linear Gaussian model based load profiling techniques that compactly capture multiple behaviors exhibited by residential customers who have traditionally been assumed to be ...The mixture model framework in ... See full document
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VOICE RECOGNITION USING ARTIFICIAL NEURAL NETWORKS AND GAUSSIAN MIXTURE MODELS AARON NICHIE
... useful applications in platforms such as access control of information, access to banking services, secured database access system, remote access to telephone services, avionics, and automobile systems, ...for ... See full document
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Enhanced Expectation–Maximization Clustering through Gaussian Mixture Models
... To invigorate speculation from a given informational index, a learning framework requires making presumptions about the theory to be educated. These suspicions are called as predispositions. Every learning ... See full document
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Gaussian Mixture Models for Human Face Recognition under Illumination Variations
... The problem of human face identification under illu- mination variations is also well-researched ([7,8]). Illu- mination changes occur frequently in real face images and hence it is imperative to develop identification ... See full document
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Dependent Gaussian mixture models for source separation
... The discovery of the cosmic microwave background (CMB) is a strong evidence for the Big Bang theory of the formation and development of the universe. Accord- ing to the theory, the early universe was ... See full document
11
Binomial Gaussian mixture filter
... a Gaussian mixture filter, such that components have smaller covariances and cause smaller linearization errors when nonlinear measurements are used for the state ...other Gaussian mixture ... See full document
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Gaussian-Induced Convolution for Graphs
... a Gaussian- induced convolution (GIC) framework to conduct local con- volution filtering on irregular ...induced Gaussian mixture model is designed to encode varia- tions of subgraph region by ... See full document
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A survey on automatic speech recognition system
... PLP is widely used in speech recognition systems as a feature extraction method. PLP similar to LPC analysis is based on the short-term spectrum of speech. In contrast to pure linear predictive analysis of speech, PLP ... See full document
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EMOTION RECOGNITION FROM SPEECH WITH GAUSSIAN MIXTURE MODELS AND VIA BOOSTED GMM
... Speech has several endowment features such as naturalness and efficient, which makes it as winsome interface medium. It is possible to express emotions and attitudes via speech. In human machine interface application ... See full document
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Analysis of a Modern Voice Morphing Approach using Gaussian Mixture Models for Laryngectomees
... This paper proposes a voicemorphing system for people suffering from Laryngectomy, which is the surgical removal of all or part of the larynx or the voice box, particularly performed in cases of laryngeal cancer. A ... See full document
6
An Overview on Speaker Identification Technologies
... using Gaussian mixtures models ...then models were built using the broad phonetic category (BPC) and the HMM-based maximum likelihood linear regression (MLLR) adaptation ... See full document
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Topics in unsupervised learning
... school leavers have come to judge their Leaving Certificates’. In past generations the vital statistic in assessing the strength of one’s Leaving Certificate was the number of passes and honours attained. Today however, ... See full document
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Gas turbine engine condition monitoring using Gaussian mixture and hidden Markov models
... This paper investigates the problem of condition monitoring of complex dynamic systems, specifically the detection, lo- calisation and quantification of transient faults. A data driven approach is developed for fault ... See full document
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Blob modification in counting vehicles using Gaussian mixture models under heavy traffic
... AI implementation on traffic light certainly requiring a process that is capable of recognizing and calculating traffic density as studied by Indrabayu et al. which uses Viola Jones method to detect and calculate the ... See full document
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Serial and parallel implementations of model based clustering via parsimonious Gaussian mixture models
... of models here suggests that the subset of variables selected by variable selection is not as good at separating the wines into type as the full range of variables ... See full document
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