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	<title>2011Arbelaez Comparison - Revision history</title>
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	<entry>
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		<title>CoSS: Created page with &quot;== Citation ==  Arbeláez, P.; Han, B.-G.; Typke, D.; Lim, J.; Glaeser, R. M. &amp; Malik, J. Experimental evaluation of support vector machine-based and correlation-based approac...&quot;</title>
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		<updated>2013-05-20T07:57:34Z</updated>

		<summary type="html">&lt;p&gt;Created page with &amp;quot;== Citation ==  Arbeláez, P.; Han, B.-G.; Typke, D.; Lim, J.; Glaeser, R. M. &amp;amp; Malik, J. Experimental evaluation of support vector machine-based and correlation-based approac...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;== Citation ==&lt;br /&gt;
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Arbeláez, P.; Han, B.-G.; Typke, D.; Lim, J.; Glaeser, R. M. &amp;amp; Malik, J. Experimental evaluation of support vector machine-based and correlation-based approaches to automatic particle selection. J. Structural Biology, 2011, 175, 319-328&lt;br /&gt;
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== Abstract ==&lt;br /&gt;
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The goal of this study is to evaluate the performance of software for automated particle-boxing, and in particular the performance of a new tool (TextonSVM) that recognizes the characteristic texture of particles of interest. As part of a high-throughput protocol, we use human editing that is based solely on class-average images to create final data sets that are enriched in what the investigator considers to be true-positive particles. The Fourier shell correlation (FSC) function is then used to characterize the homogeneity of different single-particle data sets that are derived from the same micrographs by two or more alternative methods. We find that the homogeneity is generally quite similar for class-edited data sets obtained by the texture-based method and by SIGNATURE, a cross-correlation-based method. The precision-recall characteristics of the texture-based method are, on the other hand, significantly better than those of the cross-correlation based method; that is to say, the texture-based approach produces a smaller fraction of false positives in the initial set of candidate particles. The computational efficiency of the two approaches is generally within a factor of two of one another. In situations when it is helpful to use a larger number of templates (exemplars), however, TextonSVM scales in a much more efficient way than do boxing programs that are based on localized cross-correlation.&lt;br /&gt;
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== Keywords ==&lt;br /&gt;
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Automatic particle picking, comparison of algorithms&lt;br /&gt;
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== Links ==&lt;br /&gt;
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http://www.ncbi.nlm.nih.gov/pubmed/21640190&lt;br /&gt;
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== Related software ==&lt;br /&gt;
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== Related methods ==&lt;br /&gt;
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== Comments ==&lt;/div&gt;</summary>
		<author><name>CoSS</name></author>
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