Flower Classification by Using Multiple Kernel Learning

Language	English
Type	Proceedings of International Conferences
Authors	Tomohiro Sakata, Koichi Kise
Title	Flower Classification by Using Multiple Kernel Learning
Journal	Proceedings of The 2nd China-Japan-Korea Joint Workshop on Pattern Recognition (CJKPR2010)
Pages	pp.144-147
Reviewed	Reviewed
Date	November 2010
Research fields	Pattern recognition, Object Recognition
Key	`Sakata2010` (id=1171)

Abstract

Object classification for categories with a significant visual similarity is a difficult problem. Because natural objects are slightly different for each individual, it is difficult to classify them with one feature. Therefore multiple features are needed for classification. As a method of combining multiple features, MKL has recently been focused. In this research, we employ color, shape, and texture features. We classify the flower images by using MKL and investigate the recognition rate. As a result, the best recognition rate is 75.66% in combining three features with flower 17 category dataset published by Visual Geometry Group of Oxford University.

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{authors}{authors_and}{authors_ja}{authors_ja_tight}{authors_en}{authors_en_and}{authors_tight}{first_author}{title}{title_ja}{title_en}{journal}{journal_ja}{journal_en}{book_title}{volume}{number}{series}{presen_id}{pages}{pp}{num_pages}{year}{month}{month_en}{month_short}{ym}{date}{date_ja}{date_en}{publisher}{address}{location}{review}{review_ja}{review_en}{reviewed_mark}{presen_type}{type}{type_label}{doi}{url}{key}{awards}

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@inproceedings{Sakata2010, author = {Sakata, Tomohiro and Kise, Koichi}, title = {Flower Classification by Using Multiple Kernel Learning}, booktitle = {Proceedings of The 2nd China-Japan-Korea Joint Workshop on Pattern Recognition (CJKPR2010)}, year = 2010, month = nov, pages = {144--147} }

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