Gaussian Mixture Model (GMM)
Speech to Text Converter Using Gaussian Mixture Model(GMM)
... using Gaussian Mixture ...the model, it returns one centriod for each of the cluster K and refers to the cluster number closest to ...GMM model are produced iteratively by ...
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Application of -means and Gaussian mixture model for classification of seismic activities in Istanbul
... Abstract. Two unsupervised pattern recognition algorithms, k-means, and Gaussian mixture model (GMM) analyses have been applied to classify seismic events in the vicinity of Is- tanbul. Earthquakes, ...
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ABANDONED OBJECT DETECTION IN SURVEILLANCE VIDEOUSING GAUSSIAN MIXTURE MODEL AND KALMAN FILTER
... Abandoned Object detection is most critical task in visual surveillance system. Many Public or open areas are facilitated with cameras at the multiple angles to monitor the security of that area for keeping citizens ...
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Fuzzy Weighted Gaussian Mixture Model for Feature Reduction
... Hence, Gaussian Mixture Model also plays a vital role in the form clustering initialization and it is trained by the Expectation Maximization ...component Mixture is improved by applying fuzzy ...
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Predicting Precipitation Events Using Gaussian Mixture Model
... a Gaussian mixture model (GMM) based classifier is described to tell whether precipitation events will happen on a certain day at a certain time from historical meteorological ...
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EMOTION DETECTION IN SPEECH USING GAUSSIAN MIXTURE MODEL
... A Gaussian Mixture Model (GMM) is a parametric probability density function represented as a weighted sum of Gaussian component ...parametric model of the probability distribution of ...
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Low-dimensional representation of Gaussian mixture model supervector for language recognition
... The aim of language recognition is to determine the lan- guage spoken in a given segment of speech. It is generally believed that phonotactic feature and spectral feature pro- vide complementary cues to each other [1,2]. ...
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Research on Initialization on EM Algorithm Based on Gaussian Mixture Model
... the Gaussian mixture model ( GMM ...mixed model nor the classification of the observed data, EM algorithm is a popular algorithm for estimating the parame- ters of finite mixture ...
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Adaptive Background Subtraction using Fuzzy based Gaussian Mixture Model
... the Gaussian Mixture Model (GMM) is the mostly used model due to its robustness to various challenges and good computation and memory ...requirements. Gaussian basically is a ...
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Segmentation of multi temporal images using gaussian mixture model (GMM)
... Segmentation of multi-temporal images is done using curvelet transformation & Gaussian Mixture Model (GMM). A comparison study has been made between the accuracy values of segmentation ...
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Application of Mean-Square Approximation for Piecewise Linear Optimal Compander Design for Gaussian Source and Gaussian Mixture Model
... Abstract. This paper proposes a novel piecewise linear optimal compander design method based on the mean- square approximation of the first derivative of the optimal compressor function. Designing of the piecewise linear ...
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An Emotion Recognition System based on Right Truncated Gaussian Mixture Model
... Truncated Mixture Model. In order to experiment our model we have created a data base with 200 speakers of both the genders with acted sequences of 5 different emotions, namely happy, sad, angry, ...
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SAR image change detection using Gaussian mixture model with spatial information
... Gaussian Mixture Model is one of the prevalent methods for change detection in SAR ...the model parameters in which the Maximization step is modified to incorporate the spatial ...
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Speech based Emotion Recognition with Gaussian Mixture Model
... with Gaussian mixture model (GMM model) which allows training the desired data set from the ...recognition model when large number of feature vector is ...a model is generated, ...
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Individual pig object detection algorithm based on Gaussian mixture model
... The Gaussian mixture model (GMM) is one of popular methods in the background ...models. Gaussian mixture model which applied to the pig target detection has some shortcomings ...
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Speaker Recognition using Gaussian Mixture Model
... IV. GAUSSIAN MIXTURE MODEL Definition of GMM specifies that it is the density function with probability parameters that are represented as a weighted sum of Gaussian component densities,[4] It ...
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PET image segmentation using a Gaussian mixture model and Markov random fields
... The aim of this work is to develop an automatic segmentation algorithm for PET images which is as generic as possible, i.e., threshold independent and therefore does not require system-specific regression curves or PSF. ...
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A Gaussian mixture model for automated corrosion detection in remanufacturing
... This paper presents a Gaussian mixture model (GMM) for automated corrosion detection. The GMM is used to segment corroded areas in images of automotive engines during the disassembly process. One of ...
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Medical Image Segmentation of Cardiac Quiescent by using Gaussian Mixture Model
... of life of more humans. The risk of CVD is higher when compared with all other case. This disease can be analyzed through imaging modalities such as electrocardiogram (ECG), Computed Tomography (CT), etc., But their ...
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Image segmentation-MR Images Segmentation with A Modified Gaussian Mixture Model
... Abstract---This chapter describes a method of segmenting MR images into different tissue classes, using a modified Gaussian Mixture Model. By knowing the prior spatial probability of each voxel being ...
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