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Canonical Correlation Analysis (CCA) is a well-known method for feature extraction and dimension reduction. CCA can simultaneously deal with two sets of data. It makes CCA can be used for feature level fusion. But it suffers the Small Sample Size (SSS) problem. In this paper, a new optimization criterion is presented for overcoming the SSS problem. The optimization problem can be solved analytically...
The classification for similar features classes is quite difficult task in many existing pattern-recognition systems. When the amount of samples is insufficient, neural networking training is hard. The dimension reduction, classification, clustering etc serial steps in recognition process takes such much time that the practical recognizing application is ease to meet the real time requirement. The...
Text categorization is an important research field within text mining. The initial objective of text categorization is to recognize, understand and organize various volumes of texts or documents. The general procedures of categorization are treated as supervised learning, from which the similarity can be inferred from a collection of categorized texts for training purpose. Obviously, the typical approaches...
Currently, surgery is the most effective and common way to treat cataract, one of the leading causes for blindness worldwide. Of all surgical methods, phacoemulsifieation is the most popular. During the operation, surgeons have to evaluate the hardness degree of the cataractous lens by themselves. To make the evaluation intelligent, a machine-aided classification method for cataractous lens is proposed...
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