Abstract
In the past decade, many researchers have employed various methodologies to combine decisions of multiple classifiers in order to order to improve recognition results. In this article, we will examine the main combination methods that have been developed for different levels of classifier outputs – abstract level, ranked list of classes, and measurements. At the same time, various issues, results, and applications of these methods will also be considered, and these will illustrate the diversity and scope of this research area.
Original language | English |
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Publication status | Published - Jun 2000 |
Event | The First International Workshop on Multiple Classifier System (MCS 2000) - , Italy Duration: 21 Jun 2000 → 23 Jun 2000 |
Conference
Conference | The First International Workshop on Multiple Classifier System (MCS 2000) |
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Country/Territory | Italy |
Period | 21/06/00 → 23/06/00 |