Examining cross-database global training to evaluate five different methods for ventricular beat classification

2009 ◽  
Vol 30 (7) ◽  
pp. 661-677 ◽  
Author(s):  
V Chudáček ◽  
G Georgoulas ◽  
L Lhotská ◽  
C Stylios ◽  
M Petrík ◽  
...  
2015 ◽  
Vol 62 (9) ◽  
pp. 2125-2134 ◽  
Author(s):  
Julien Oster ◽  
Joachim Behar ◽  
Omid Sayadi ◽  
Shamim Nemati ◽  
Alistair E. W. Johnson ◽  
...  

2022 ◽  
Vol 70 (3) ◽  
pp. 4503-4521
Author(s):  
Shubha Sumesh ◽  
John Yearwood ◽  
Shamsul Huda ◽  
Shafiq Ahmad

2014 ◽  
Vol 687-691 ◽  
pp. 3917-3922
Author(s):  
Yi Chang Wang ◽  
Feng Qi Yan ◽  
Yu Fang

ECG signal contains abundant information of human heart activity. It is important basis of doctors’ diagnose. With the development of computer technology, computer aided analysis has been widely applied in the field of ECG analysis. Most of the traditional method is based on single classifier and too complex. Also, the accuracy is not high. This paper focuses on ECG heart beat classification, extracting different types of feature, training different classifiers by vector model and support vector machine (SVM), merging the result of multiple classifiers. In this paper, we used the advanced voting method (voting by weight) to fusion the result of different classifier, having compared it with the traditional voting method.It performed better than traditional method in term of accuracy


2013 ◽  
Vol 5 (1) ◽  
pp. 57
Author(s):  
Marie Sadron ◽  
Alexandre Duparc ◽  
Pierre Mondoly ◽  
Anne Rollin ◽  
Marc Delay ◽  
...  

2002 ◽  
Vol 31 (3) ◽  
pp. 309-316 ◽  
Author(s):  
John L. Daly

At the dawn of the 21st Century, there is growing interest in the sharing of policy and management “success” stories and innovative training methodologies. This is an important part of addressing public policy problems. Global training is gaining increased application especially in underdeveloped nations. This article offers eight strategies for increased participant acceptance of training when provided in other cultural settings.


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