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Titlebook: Structural, Syntactic, and Statistical Pattern Recognition; Joint IAPR Internati Georgy Gimel’farb,Edwin Hancock,Keiji Yamada Conference pr

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0302-9743 pattern recognition, clustering, learning, kernel methods in statistical pattern recognition, kernel methods in statistical pattern recognition, as well as applications of structural, syntactical, and statistical methods.978-3-642-34165-6978-3-642-34166-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
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978-3-642-34165-6Springer-Verlag GmbH Germany, part of Springer Nature 2012
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Structural, Syntactic, and Statistical Pattern Recognition978-3-642-34166-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/t/image/880092.jpg
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A Clustering-Based Ensemble Technique for Shape Decompositioning-based approach is proposed to determine a final decomposition from an ensemble of input decompositions. A recently published performance evaluation framework consisting of a benchmark database with manual ground truth together with evaluation measures is used to demonstrate the benefit of the proposed ensemble technique.
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