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Davis King 2015-02-28 14:34:57 -05:00
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@ -2919,13 +2919,10 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
<a href="imaging.html#scan_image_custom">scan_image_custom</a> object.
<p>
It learns the parameter vector by formulating the problem as a <a href="#structural_svm_problem">structural
SVM problem</a>. The general approach is similar to the method discussed in
Learning to Localize Objects with Structured Output Regression by
Matthew B. Blaschko and Christoph H. Lampert. However, the method has
been extended to datasets with multiple, potentially overlapping, objects
per image and the measure of loss is different from what is described in
the paper.
It learns the parameter vector by formulating the problem as a <a
href="#structural_svm_problem">structural SVM problem</a>.
The exact details of the method are described in the paper
<a href="http://arxiv.org/abs/1502.00046">Max-Margin Object Detection</a> by Davis E. King.
</p>
</description>