Learning and intelligence can happen everywhere, a case study: learning via Non-uniform 1D rulers with applications in image classification and recognition

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• 作者：Yizhen Huang ; Yepeng Guan
• 关键词：Parameter learning ; Image classification ; Recognition
• 刊名：Multimedia Tools and Applications
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：76
• 期：1
• 页码：913-929
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：Multimedia Information Systems; Computer Communication Networks; Data Structures, Cryptology and Information Theory; Special Purpose and Application-Based Systems;
• 出版者：Springer US
• ISSN：1573-7721
• 卷排序：76

文摘

In this paper, we presented a non-uniform 1D ruler model and applied it in various image classification and image recognition scenarios, and some are for military technology usage. Our model is very simple, elegant and original, which is solved by convex quadratic programming. It has wide applications in pattern recognition and intelligent multimedia data analysis. We believe that a new research topic, namely, numeric calibration, has started, which is parallel to dimensionality reduction, feature selection, or metric learning etc. Our methods can be used as a pre-processing step for metric learning methods, in which, our learned calibrated feature space is used as input for them. The various combinations of our methods and metric learning methods, may lead to new interesting research problems.