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Abstract: We show via an equivalence of mathematical programs that a support vector (SV) algorithm can be translated into an equivalent boosting-like algorithm and vice versa. We exemplify this translation procedure for a new algorithm -- one-class leveraging -- starting from the one-class support vector machine (1-SVM). This is a first step towards unsupervised learning in a boosting framework. Building on so-called barrier methods known from the theory of constrained optimization, it returns a... (Update)
Context of citations to this paper: More
...resolution, when it is not low enough to have roads as lines, by resampling the image. 2. Extraction of lines using Steger s algorithm [15], which is presented in Section 3. 3. Using the results of the line detection step, we find location of line junctions (Section 4) 4....
...resolution, when it is not low enough to have roads as lines, by re sampling the image. 2. Extraction of lines using Steger s algorithm [16]. 3. Using the results of the line detection step, we find location of line junctions. 4. Matching the extremities of road segments with...
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BibTeX entry: (Update)
Steger, C., 1998a. An unbiased detector of curvilinear structures. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(2), pp. 113--125. http://citeseer.ist.psu.edu/530291.html More
@misc{ steger-ieee,
author = "C. Steger",
title = "IEEE Transactions on Pattern Analysis and Machine Intelligence",
text = "Steger, C., 1998a. An unbiased detector of curvilinear structures. IEEE
Transactions on Pattern Analysis and Machine Intelligence 20(2), pp. 113--125.",
url = "citeseer.ist.psu.edu/530291.html" }
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