Presentation 2003/10/16
Generic Image Classification by Web Image Mining : Experiments Using a Large Number of Web Images
Keiji YANAI,
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Abstract(in English) Thanks to the recent rapid spread of digital imaging devices, the demand for generic image recognition of various kinds of scenes becomes greater. Ilt is, however, hard to collect various kinds of training images for recognition of various kinds of scenes so far. To solve this problem, we have proposed a generic image classification system with an automatic knowledge acquisition mechanism from the World Wide Web (WWW). We call this knowledge acquisition from WWW "Web image mining". The system gathers a large number of images related to given class keywords from the Web and classifies an unknown image into one of the classes corresponding to the class keywords using gathered images as training ones. In this report, we describe how to gather more than one thousand images per class and the experimental results of image classification by using a large number of training images.
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Keyword(in English) Web image mining / image gathering / image classification / WWW / image retrieval / image database
Paper # PRMU2003-120,NC2003-51
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Committee NC
Conference Date 2003/10/16(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Generic Image Classification by Web Image Mining : Experiments Using a Large Number of Web Images
Sub Title (in English)
Keyword(1) Web image mining
Keyword(2) image gathering
Keyword(3) image classification
Keyword(4) WWW
Keyword(5) image retrieval
Keyword(6) image database
1st Author's Name Keiji YANAI
1st Author's Affiliation Department of Computer Science, The University of Electro-Communications()
Date 2003/10/16
Paper # PRMU2003-120,NC2003-51
Volume (vol) vol.103
Number (no) 391
Page pp.pp.-
#Pages 6
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