Results 31 to 40 of about 901,615 (325)

Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing. [PDF]

PLoS ONE, 2017
This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation.
Siow Hoo Leong, Seng Huat Ong
doaj   +1 more source

Extensible Gaussian Mixture Model for Image Prior Modeling [PDF]

Jisuanji gongcheng, 2020
To address the inextensible fixed number of components in image prior modeling based on Gaussian Mixture Model(GMM),this paper proposes an extensible GMM model based on Dirichlet Process(DP).Through the addition and merging mechanism of cluster ...
ZHANG Mohua, PENG Jianhua
doaj   +1 more source

Scale-Based Gaussian Coverings: Combining Intra and Inter Mixture Models in Image Segmentation

Entropy, 2009
By a “covering” we mean a Gaussian mixture model fit to observed data. Approximations of the Bayes factor can be availed of to judge model fit to the data within a given Gaussian mixture model.
Jean-Luc Starck, Fionn Murtagh, Pedro Contreras   +2 more
doaj   +1 more source

Mixtures of Shifted Asymmetric Laplace Distributions [PDF]

, 2012
A mixture of shifted asymmetric Laplace distributions is introduced and used for clustering and classification. A variant of the EM algorithm is developed for parameter estimation by exploiting the relationship with the general inverse Gaussian ...
Browne, Ryan P., Franczak, Brian C., McNicholas, Paul D.   +2 more
core   +1 more source

Short-term forecasting and uncertainty analysis of wind turbine power based on long short-term memory network and Gaussian mixture model

Applied Energy, 2019
Wind power plays a leading role in the development of renewable energy. However, the random nature of wind turbine power and its associated uncertainty create challenges in dispatching this power effectively in the power system, which can result in ...
Jinhua Zhang, Jie Yan, D. Infield, Yongqian Liu, F. Lien   +4 more
semanticscholar   +1 more source

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

Ensemble image registration by a spatially constrained clustering approach

International Journal of Advanced Robotic Systems, 2016
In this article, a novel spatially constrained clustering approach is proposed for ensemble image registration. We use a spatially constrained Gaussian mixture model, which is based on a joint Gaussian mixture model and Markov random field, to model the ...
Hao Zhu, Qiqun Shi, Yongfu Li, Qiuxuan Wu   +3 more
doaj   +1 more source

Infinite Mixtures of Multivariate Gaussian Processes [PDF]

, 2013
This paper presents a new model called infinite mixtures of multivariate Gaussian processes, which can be used to learn vector-valued functions and applied to multitask learning.
Sun, Shiliang
core   +1 more source

Statistical characterization of full-margin rupture recurrence for Cascadia subduction zone using event time resampling and Gaussian mixture model

Geoscience Letters, 2023
Earthquake occurrence modeling of large subduction events involves significant uncertainty, stemming from the scarcity of geological data and inaccuracy of dating techniques.
Katsuichiro Goda
doaj   +1 more source

Variational learning for Gaussian mixture models [PDF]

IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 2006
This paper proposes a joint maximum likelihood and Bayesian methodology for estimating Gaussian mixture models. In Bayesian inference, the distributions of parameters are modeled, characterized by hyperparameters. In the case of Gaussian mixtures, the distributions of parameters are considered as Gaussian for the mean, Wishart for the covariance, and ...
Nikolaos, Nasios, Adrian G, Bors
openaire   +2 more sources