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  • 标题:Texture Classification using Na?ve Bayes Classifier
  • 本地全文:下载
  • 作者:Ayman M Mansour
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2018
  • 卷号:18
  • 期号:1
  • 页码:112-120
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:This paper presents a texture classification algorithm using Independent Component Analysis and Na?ve Bayes Classifier. Na?ve Bayes is one of the most effective and efficient classification algorithms. Na?ve Bayes classifiers still tend to perform very well under unrealistic assumption. Especially for small sample sizes, naive Bayes classifiers can outperform the more powerful classifiers. Texture features are extracted using Independent Component Analysis and then classified by Na?ve Bayes Classifier. Experiments were performed in order to evaluate the performance of the proposed classifier. It consists of texture images from the Describable Textures Dataset (DTD) and Brodatz album. Experimental results show that the proposed algorithm has an encouraging performance. The Na?ve Bayes Classifier produces a very accurate classification results.
  • 关键词:;;;; ;;;;;; Na?ve Bayes; feature; Independent Component; Classifier.
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