Results 221 to 230 of about 102,586 (261)

Identifying Physical Interactions in Contact‐Based Robot Manipulation for Learning from Demonstration

Advanced Robotics Research, EarlyView.
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek, Herman van der Kooij, Douwe Dresscher, Mark Vlutters   +3 more
wiley   +1 more source

Improving resolution and resolvability of single-particle cryoEM structures using Gaussian mixture models. [PDF]

Nat Methods
Chen M, Schmid MF, Chiu W.
europepmc   +1 more source

Improvement of the Gaussian mixture models' unsupervised learning method through the inclusion of dynamical systems for various types of nonlinear data. [PDF]

Heliyon
Mahjoub R.
europepmc   +1 more source

Novel gene-specific Bayesian Gaussian mixture model to predict the missense variants pathogenicity of Sanfilippo syndrome. [PDF]

Sci Rep
Mohammed EEA, Fayez AG, Abdelfattah NM, Fateen E.   +3 more
europepmc   +1 more source

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Fuzzy Gaussian Mixture Models

Pattern Recognition, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhaojie Ju, Honghai Liu
exaly   +3 more sources

SAR images as mixtures of Gaussian mixtures

IEEE International Conference on Image Processing 2005, 2005
We consider the problem of image segmentation by clustering local histograms with parametric mixture-of-mixture models. These models represent each cluster by a single mixture model of simple parametric components, typically truncated Gaussians. Clustering requires unsupervised inference of the model parameters, for which we derive a nested variant of ...
Peter Orbanz, Joachim M. Buhmann
openaire   +1 more source

Gaussian Mixture Descriptors Learner

Knowledge-Based Systems, 2020
Abstract In recent decades, various machine learning methods have been proposed to address classification problems. However, most of them do not support incremental (or online) learning and therefore are neither scalable nor robust to dynamic problems that change over time.
Breno L. Freitas, Renato Moraes Silva, Tiago A. Almeida 0001   +2 more
openaire   +1 more source

Correlation of Gaussian Mixture Tracks

2018 21st International Conference on Information Fusion (FUSION), 2018
In this paper, methods are developed and evaluated for the correlation of Gaussian mixture tracks from two sensors. The hypothesis likelihoods for the case of a single target are given using the minimum mean square error and the maximum likelihood estimates of common origin between two Gaussian mixtures.
Terrence L. Ogle, Ben P. Davis, William Dale Blair, Peter K. Willett   +3 more
openaire   +1 more source

Learning mixtures of Gaussians

40th Annual Symposium on Foundations of Computer Science (Cat. No.99CB37039), 2003
Mixtures of Gaussians are among the most fundamental and widely used statistical models. Current techniques for learning such mixtures from data are local search heuristics with weak performance guarantees. We present the first provably correct algorithm for learning a mixture of Gaussians.
openaire   +1 more source