Automatic glaucoma screening hybrid cloud system with pattern classification algorithms

Author(s):  
Ying Quan ◽  
Jun Cheng ◽  
Beng Hai Lee ◽  
Ai Ping Yow ◽  
Damon Wing Kee Wong
2017 ◽  
Vol 2017 (13) ◽  
pp. 2203-2206 ◽  
Author(s):  
Daohua Zhu ◽  
Yajuan Guo ◽  
Jinming Chen ◽  
Yan Li ◽  
Haitao Jiang

Author(s):  
Nabarun Bhattacharyya ◽  
Bipan Tudu ◽  
Rajib Bandyopadhyay

Because of these factors, it is necessary to make the system flexible in such a way that the system is able to update an existing classifier without affecting the classification performance on old data, and such classifiers should have the property as being both stable and plastic. Conventional pattern classification algorithms require the entire dataset during training, and thereby fail to meet the criteria of being plastic and stable at the same time. The incremental learning algorithms possess these features, and thus, the electronic nose systems become extremely versatile when equipped with these classifiers. In this chapter, the authors describe different incremental learning algorithms for machine olfaction.


2008 ◽  
Vol 42 (22) ◽  
pp. 8486-8491 ◽  
Author(s):  
Tal Elad ◽  
Etay Benovich ◽  
Sagi Magrisso ◽  
Shimshon Belkin

2017 ◽  
Vol 32 (5) ◽  
pp. 974-990 ◽  
Author(s):  
Wen-Min Li ◽  
Xue-Lei Li ◽  
Qiao-Yan Wen ◽  
Shuo Zhang ◽  
Hua Zhang

1968 ◽  
Vol 56 (12) ◽  
pp. 2101-2114 ◽  
Author(s):  
Yu-Chi Ho ◽  
A.K. Agrawala

2013 ◽  
Vol 3 (4) ◽  
pp. 23
Author(s):  
Irina Pavlovna Bolodurina ◽  
Alexander Evegenevich Shukhman ◽  
Denis Igorevich Parfenov

This article presents a model of queuing system for broadband multimedia educational resources, as well as a model of access to a hybrid cloud system storage. These models are used to enhance the efficiency of computing resources in a distance learning system. An additional OpenStack control module has been developed to achieve the distribution of request streams and balance the load between cloud nodes.


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