Matrix exponential based semi-supervised discriminant embedding for image classification
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- 作者：F. Dornaikaa ; b ; Author Vitae ; Y. El TraboulsiaAuthor Vitae
- 关键词：Graph-based semi-supervised learning ; Small-sample-size (SSS) problem ; Matrix exponential ; Semi-supervised discriminant embedding (SDE) ; Distance diffusion mapping ; Feature extraction ; Image classification
- 刊名：Pattern Recognition
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：61
- 期：Complete
- 页码：92-103
- 全文大小：1296 K
文摘
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An exponential semi-supervised discriminant embedding is proposed.
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It solves the small-sample-size problem.
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It enhances the discrimination between different classes.
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Classification performance after embedding is assessed on seven public image datasets.
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Performance is studied using several types of image descriptors.
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