摘要
In various application areas of pattern recognition, combing multiple classifiers is regarded as a new method for achieving a substantial gain in performance of systems. This paper discusses the properties of the diversity of classifiers and its applications. At the same time, the paper presents a novel method for combining multiple classifiers based on the diversity. Fusion strategies are discussed for providing a basis for combing classifiers. These combination strategies are experimentally tested on online handwritten Chinese character recognition system and their effectiveness is considered.
In various application areas of pattern recognition, combing multiple classifiers is regarded as a new method for achieving a substantial gain in performance of systems. This paper discusses the properties of the diversity of classifiers and its applications. At the same time, the paper presents a novel method for combining multiple classifiers based on the diversity. Fusion strategies are discussed for providing a basis for combing classifiers. These combination strategies are experimentally tested on online handwritten Chinese character recognition system and their effectiveness is considered.
基金
SupportedbytheNationalNaturalScienceFoundationofChinaandtheScientificResearchFoundationofHarbinInstituteofTechnology