Results 281 to 290 of about 901,615 (325)

Ensemble unsupervised autoencoders and Gaussian mixture model for cyberattack detection

Information Processing & Management, 2022
Peng An, Zhiyuan Wang, Chunjiong Zhang
semanticscholar   +1 more source

Combining Gaussian Mixture Models

2004
A Gaussian mixture model (GMM) estimates a probability density function using the expectation-maximization algorithm. However, it may lead to a poor performance or inconsistency. This paper analytically shows that performance of a GMM can be improved in terms of Kullback-Leibler divergence with a committee of GMMs with different initial parameters ...
Hyoung-joo Lee, Sungzoon Cho
openaire   +1 more source

Outlier Detection Algorithm Based on Gaussian Mixture Model

2019 IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS), 2019
Outlier detection is an important aspect in the field of data mining. In order to solve the problem of outlier detection in high-dimensional datasets, an outlier detection algorithm based on Gaussian mixture model is proposed.
Wenbo Liu, Delong Cui, Zhiping Peng, Jihai Zhong   +3 more
semanticscholar   +1 more source

Gaussian Mixture Models

The slides introduce Gaussian Mixture Models (GMMs) and extend to mixtures of Bernoulli distributions. They begin with the formulation of GMMs as weighted sums of Gaussian components, describing latent variables, prior and conditional distributions, and posterior responsibilities.
openaire   +1 more source

Gaussian Mixture Model Cluster Forest

2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA), 2015
Random Forest (RF) classification algorithm is widely used in the area of information retrieval and became a basis for some extended branches of classification and/or regression algorithms. Cluster Forest (CF) represents a particular branch, and brings usually better results than individual clustering algorithms.
Jan Janouek, Petr Gajdo, Michal Radecky, Vaclav Snael   +3 more
openaire   +1 more source

Novel cascaded Gaussian mixture model-deep neural network classifier for speaker identification in emotional talking environments

Neural computing & applications (Print), 2018
This research is an effort to present an effective approach to enhance text-independent speaker identification performance in emotional talking environments based on novel classifier called cascaded Gaussian Mixture Model-Deep Neural Network (GMM-DNN ...
I. Shahin, Ali Bou Nassif, Shibani Hamsa
semanticscholar   +1 more source

Splitting Gaussians in Mixture Models

2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance, 2012
Gaussian mixture models have been extensively used and enhanced in the surveillance domain because of their ability to adaptively describe multimodal distributions in real-time with low memory requirements. Nevertheless, they still often suffer from the problem of converging to poor solutions if the main mode stretches and thus over-dominates weaker ...
Ruben Heras Evangelio, Michael Patzold, Thomas Sikora   +2 more
openaire   +1 more source

Improved adaptive Gaussian mixture model for background subtraction

Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004., 2004
Z. Zivkovic
semanticscholar   +1 more source

Antibody–drug conjugates: Smart chemotherapy delivery across tumor histologies

Ca-A Cancer Journal for Clinicians, 2022
Paolo Tarantino, Roberto Carmagnani Pestana, Shanu Modi   +2 more
exaly  

Visualizing Gaussian Mixture Models

2023
Luca Scrucca, Chris Fraley, T. Brendan Murphy, Adrian E. Raftery   +3 more
openaire   +1 more source