Results 11 to 20 of about 34,052 (223)
Convex hull indexed Gaussian mixture model (CH-GMM) for 3D point set registration [PDF]
Pattern Recognition, 2016 To solve the problem of rigid/non-rigid 3D point set registration, a novel convex hull indexed Gaussian mixture model (CH-GMM) is proposed in this paper. The model works by computing a weighted Gaussian mixture model (GMM) response over the convex hull of each point set.
Jingfan Fan +6 more
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Improved Bearings-Only Multi-Target Tracking with GM-PHD Filtering
Sensors, 2016 In this paper, an improved nonlinear Gaussian mixture probability hypothesis density (GM-PHD) filter is proposed to address bearings-only measurements in multi-target tracking.
Qian Zhang, Taek Lyul Song
doaj +1 more source
Porting concepts from DNNs back to GMMs [PDF]
, 2013 Deep neural networks (DNNs) have been shown to outperform Gaussian Mixture Models (GMM) on a variety of speech recognition benchmarks. In this paper we analyze the differences between the DNN and GMM modeling techniques and port the best ideas from the ...
Demuynck, Kris, Triefenbach, Fabian
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Meikuang Anquan, 2020 An online detection method for longitudinal tear of mine conveyor belt is proposed, and the method combines infrared image features with improved Gaussian Mixture Model(GMM). An adaptive hybrid median filtering technique is designed.
GUO Jian, QIAO Tiezhu, CHE Jian
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Surrogate modeling approximation using a mixture of experts based on EM joint estimation [PDF]
, 2010 An automatic method to combine several local surrogate models is presented. This method is intended to build accurate and smooth approximation of discontinuous functions that are to be used in structural optimization problems.
Bartoli, Nathalie +4 more
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S-TRANSFORM AND GAUSSIAN MIXTURE MODEL FOR ACOUSTIC SCENE CLASSIFICATION
International Journal of Advances in Signal and Image Sciences, 2020 In this study, Acoustic Scene Classification (ASC) system is designed with the help of S-transform and Gaussian Mixture Model (GMM). The S-transform is an extension of continuous wavelet transform that combines the progressive resolution with phase ...
Santosh Kumar Srivastava
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Automatic Speaker Recognition with Multi-Resolution Gaussian Mixture Models (MR-GMM) [PDF]
The International Journal of Forensic Computer Science, 2009 Gaussian Mixture Models (GMMs) are the most widely used technique for voice modeling in automatic speaker recognition systems. In this paper, we introduce a variation of the traditional GMM approach that uses models with variable complexity (resolution).
D’Almeida, Frederico Quadros +3 more
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Clustering compositional data using Dirichlet mixture model.
PLoS ONE, 2022 A model-based clustering method for compositional data is explored in this article. Most methods for compositional data analysis require some kind of transformation. The proposed method builds a mixture model using Dirichlet distribution which works with
Samyajoy Pal, Christian Heumann
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Kernel Analysis Based on Dirichlet Processes Mixture Models
Entropy, 2019 Kernels play a crucial role in Gaussian process regression. Analyzing kernels from their spectral domain has attracted extensive attention in recent years. Gaussian mixture models (GMM) are used to model the spectrum of kernels.
Jinkai Tian, Peifeng Yan, Da Huang
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Statistical Compressed Sensing of Gaussian Mixture Models [PDF]
, 2011 A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribution, and achieving accurate reconstruction on average, is introduced.
Sapiro, Guillermo, Yu, Guoshen
core +2 more sources