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Humans have the capability to recognize family members. Phrases such as “John has his father's nose” or “Joe has his mother's eyes” are quite common. Motivated by this, we consider the following question: Is it possible to develop a method to extract the salient familial traits in face images for kinship recognition? If this idea works, an instrument may be invented to measure familial relationships...
Recently, we have proposed a handwriting Chinese character database HIT-OR3C. Though it has been introduced in detail, to date, it has not been evaluated by any handwriting recognition method. To help the researchers use this database for algorithm evaluation, we propose the structure of HIT-OR3C database. Moreover, we evaluate the OR3C database with a series of experiments using state-of-the-art...
Although Support Vector Machines(SVM) succeed in classifying several image databases using image descriptors proposed in the literature, no single descriptor can be optimal for general object categorization. This paper describes a novel framework to learn the optimal combination of kernels corresponding to multiple image descriptors before SVM training, leading to solve a quadratic programming problem...
Classical text clustering algorithms are usually based on vector space model or its variants. Because of the high computing complexity and the difficulty of controlling clustering results, this kind of approaches are hard to be applied for the purpose of the large scale text clustering. Clustering algorithms based on frequent term sets make use of relationship among documents and their shared frequent...
Document genre information is one of the most distinguishing features in information retrieval, which brings order to the search results. What the genre classification concerned is not the topic but the genre of document. In this paper, we examine the effectiveness of using machine learning techniques to solve genre classification of Chinese text with the same topic, viz. finance. Based on the likelihood...
Text clustering techniques were usually used to structure the text documents into topic related groups which can facilitate users to get a comprehensive understanding on corpus or results from information retrieval system. Most of existing text clustering algorithm which derived from traditional formatted data clustering heavily rely on term analysis methods and adopted vector space model (VSM) as...
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