Results 81 to 90 of about 942,483 (302)
Parameter estimation of two dimensional component Gaussian mixtures [PDF]
, 2003 Multiresolution Gaussian Mixture Models (MGMM) can be used to represent image and video data in video annotation and retrieval. Preliminary experiments were carried out to estimate the model parameters for two-dimensional data.
Katugampala, Nilantha, Wilson, Roland
core
Convex comparison of Gaussian mixtures
Journal of Multivariate AnalysisMotivated by the study of the propagation of convexity by semi-groups of stochastic differential equations and convex comparison between the distributions of solutions of two such equations, we study the comparison for the convex order between a Gaussian distribution and a Gaussian mixture.
Jourdain, Benjamin, Pagès, Gilles
openaire +3 more sources
Estimation of a 3D motion field from a multi-camera array using a multiresolution Gaussian mixture model [PDF]
, 2008 The problem of modelling geometry for video based rendering has been much studied in recent years, due to the growing interest in 'free viewpoint' video and similar applications.
Mullins, A. +7 more
core
Sparse Multivariate Gaussian Mixture Regression [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2015 Fitting a multivariate Gaussian mixture to data represents an attractive, as well as challenging problem, in especial when sparsity in the solution is demanded. Achieving this objective requires the concurrent update of all parameters (weight, centers, and precisions) of all multivariate Gaussian functions during the learning process. Such is the focus
Luis Weruaga, Javier Vía
openaire +4 more sources
Advanced Engineering Materials, EarlyView.We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
wiley +1 more source
Density Estimation Using Mixtures of Mixtures of Gaussians [PDF]
, 2006 In this paper we present a new density estimation algorithm using mixtures of mixtures of Gaussians. The new algorithm overcomes the limitations of the popular Expectation Maximization algorithm. The paper first introduces a new model selection criterion called the Penalty-less Information Criterion, which is based on the Jensen-Shannon divergence ...
Wael Abd-Almageed, Larry S. Davis
openaire +2 more sources
Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying
Advanced Engineering Materials, EarlyView.An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara +8 more
wiley +1 more source
In Situ Micromechanical Study of Bimodal γ′–γ″ Precipitate Assemblies in Ni–Cr–Al–Nb Superalloy
Advanced Engineering Materials, EarlyView.A Ni–Cr–Al–Nb superalloy with a bimodal γ′–γ″ precipitate distribution is developed. Composite precipitate assemblies form through heterogeneous nucleation, effectively impeding dislocation motion. Micropillar compression reveals high strength at room and elevated temperatures, governed by precipitate shearing, with coupled faulting mechanisms ...
Ujjval Bansal +4 more
wiley +1 more source
Copula models in machine learning [PDF]
, 2015 The introduction of copulas, which allow separating the dependence structure of a multivariate distribution from its marginal behaviour, was a major advance in dependence modelling.
Rey, Mélanie
core +1 more source
Study on driver’s turning intention recognition hybrid model of GHMM and GGAP-RBF neural network
Advances in Mechanical Engineering, 2018 The accuracy and real time are crucial in turning intention recognition. Therefore, a hybrid model of Gaussian mixture hidden Markov and generalized growing and pruning algorithm for radial basis function neural network is constructed to recognize driver
Shu Wang, Qiang Yu, Xuan Zhao
doaj +1 more source