Semi-supervised variational Bayesian Student'st mixture regression and robust inferential sensor application
Data-driven inferential sensor has been widely adopted to estimate key quality relevant
variables. However, industrial dataset usually presents many characteristics such as …
variables. However, industrial dataset usually presents many characteristics such as …
Student's-t Mixture Regression-Based Robust Soft Sensor Development for Multimode Industrial Processes
Because of multiple manufacturing phases or operating conditions, a great many industrial
processes work with multiple modes. In addition, it is inevitable that some measurements of …
processes work with multiple modes. In addition, it is inevitable that some measurements of …
Fast and adaptive deep fusion learning for detecting visual objects
N Doulamis, A Doulamis - Computer Vision–ECCV 2012. Workshops and …, 2012 - Springer
Currently, object tracking/detection is based on a “shallow learning” paradigm; they locally
process features to build an object model and then they apply adaptive methodologies to …
process features to build an object model and then they apply adaptive methodologies to …
A mixture model approach for formant tracking and the robustness of student's-t distribution
H Sundar, CS Seelamantula… - IEEE transactions on …, 2012 - ieeexplore.ieee.org
We address the problem of robust formant tracking in continuous speech in the presence of
additive noise. We propose a new approach based on mixture modeling of the formant …
additive noise. We propose a new approach based on mixture modeling of the formant …
Student's t-distribution mixture background model for efficient object detection
L Guo, M Du - 2012 IEEE International Conference on Signal …, 2012 - ieeexplore.ieee.org
Background subtraction is an essential technique for moving object segmentation in vision
surveillance system. To acquire an exact background, Gaussian mixture modeling (GMM) is …
surveillance system. To acquire an exact background, Gaussian mixture modeling (GMM) is …
Unsupervised image categorization based on variational autoencoder and student'st mixture model
Y Zhang, W Fan, N Bouguila - 2019 IEEE Symposium Series on …, 2019 - ieeexplore.ieee.org
In this work, a novel generative robust image catego-rization approach is developed based
on variational autoencoder (VAE) and Student's-T Mixture Model (STMM). The network …
on variational autoencoder (VAE) and Student's-T Mixture Model (STMM). The network …