Performance of the StaphGold ELISA test in determining subclinical Staphylococcus aureus infections in dairy cows using a Gaussian mixture model
Sign Up to like & getrecommendations! Published in 2022 at "Veterinary Medicine and Science"
DOI: 10.1002/vms3.785
Abstract: Abstract Background A novel ELISA test has been developed to detect antigen‐specific IgG in early and late lactation cows in New Zealand. Objectives This study was to evaluate the discriminatory ability of the ELISA based… read more here.
Keywords: using gaussian; elisa test; test; mixture model ... See more keywords
Bayesian Gaussian Mixture Linear Inversion for Geophysical Inverse Problems
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DOI: 10.1007/s11004-016-9671-9
Abstract: A Bayesian linear inversion methodology based on Gaussian mixture models and its application to geophysical inverse problems are presented in this paper. The proposed inverse method is based on a Bayesian approach under the assumptions… read more here.
Keywords: geophysical inverse; linear inversion; inversion; gaussian mixture ... See more keywords
Performance enhancement of salient object detection using superpixel based Gaussian mixture model
Sign Up to like & getrecommendations! Published in 2017 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-017-4748-0
Abstract: Humans possess an intelligent system which effortlessly detect salient objects with high accuracy in real-time. It is a challenge to develop a computational model which can mimic human behavior such that the model achieves better… read more here.
Keywords: mixture model; detection; proposed model; time ... See more keywords
Gradient-Based Training of Gaussian Mixture Models for High-Dimensional Streaming Data
Sign Up to like & getrecommendations! Published in 2021 at "Neural Processing Letters"
DOI: 10.1007/s11063-021-10599-3
Abstract: We present an approach for efficiently training Gaussian Mixture Model (GMM) by Stochastic Gradient Descent (SGD) with non-stationary, high-dimensional streaming data. Our training scheme does not require data-driven parameter initialization (e.g., k-means) and can thus… read more here.
Keywords: high dimensional; streaming data; gaussian mixture; training gaussian ... See more keywords
Deep Gaussian mixture models
Sign Up to like & getrecommendations! Published in 2019 at "Statistics and Computing"
DOI: 10.1007/s11222-017-9793-z
Abstract: Deep learning is a hierarchical inference method formed by subsequent multiple layers of learning able to more efficiently describe complex relationships. In this work, deep Gaussian mixture models (DGMM) are introduced and discussed. A DGMM… read more here.
Keywords: mixture; deep gaussian; mixture models; gaussian mixture ... See more keywords
Embedded task system and Gaussian mixture model in the analysis and application of user behavior in marketing management
Sign Up to like & getrecommendations! Published in 2021 at "Wireless Networks"
DOI: 10.1007/s11276-021-02697-w
Abstract: With the rapid development of science and technology, embedded mission systems have also penetrated into various industries such as scientific research and military technology. The more and more complex tasks and higher frequency of use… read more here.
Keywords: mixture model; company; marketing management; marketing ... See more keywords
Computer-assisted delineation of cerebral infarct from diffusion-weighted MRI using Gaussian mixture model
Sign Up to like & getrecommendations! Published in 2017 at "International Journal of Computer Assisted Radiology and Surgery"
DOI: 10.1007/s11548-017-1520-x
Abstract: PurposeDiffusion-weighted imaging (DWI) is a widely used medical imaging modality for diagnosis and monitoring of cerebral stroke. The identification of exact location of stroke lesion helps in perceiving its characteristics, an essential part of diagnosis… read more here.
Keywords: mixture model; methodology; stroke lesion; computer assisted ... See more keywords
A Gaussian mixture model based combined resampling algorithm for classification of imbalanced credit data sets
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Machine Learning and Cybernetics"
DOI: 10.1007/s13042-019-00953-2
Abstract: Credit scoring represents a two-classification problem. Moreover, the data imbalance of the credit data sets, where one class contains a small number of data samples and the other contains a large number of data samples,… read more here.
Keywords: credit data; data sets; credit; classification ... See more keywords
Adaptive design of experiments based on Gaussian mixture regression
Sign Up to like & getrecommendations! Published in 2021 at "Chemometrics and Intelligent Laboratory Systems"
DOI: 10.1016/j.chemolab.2020.104226
Abstract: Abstract In the design of molecules, materials, and processes, adaptive design of experiments (ADoE) is conducted to minimize the number of experiments. Although Bayesian optimization (BO) is an effective tool, BO merely selects a candidate… read more here.
Keywords: number; mixture regression; gaussian mixture; design experiments ... See more keywords
Remaining energy estimation for lithium-ion batteries via Gaussian mixture and Markov models for future load prediction
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DOI: 10.1016/j.est.2020.101271
Abstract: Abstract Other than upgrading the energy storage technology employed within electric vehicles (EVs), improving the driving range estimation methods will help to reduce the phenomena, known as range anxiety. The remaining discharge energy (RDE) of… read more here.
Keywords: energy; load prediction; battery; gaussian mixture ... See more keywords
Augmenting deviation of faults from the normal using fault assistant Gaussian mixture prior variational autoencoder
Sign Up to like & getrecommendations! Published in 2021 at "Journal of the Taiwan Institute of Chemical Engineers"
DOI: 10.1016/j.jtice.2021.06.015
Abstract: Abstract In this new era of Industry 4.0, manufacturers tend to store process data from the entire production, regardless of whether they are “normal” or “faulty” for further data analysis. However, almost all the existing… read more here.
Keywords: prior variational; variational autoencoder; mixture prior; fault ... See more keywords