Hough transform based object detectors learn a mapping from the image domain to a Hough voting space. Within this space, object hypotheses are formed by local maxima. The votes con...
Object oriented programming promotes reuse of classes in multiple contexts. Thus, a class is designed and implemented with several usage scenarios in mind, some of which possibly ...
A fast simulatedannealingalgorithmis developed for automatic object recognition. The object recognition problem is addressed as the problem of best describing a match between a hy...
The k-Nearest Neighbors algorithm can be easily adapted to classify complex objects (e.g. sets, graphs) as long as a proper dissimilarity function is given over an input space. Bo...
Adam Woznica, Alexandros Kalousis, Melanie Hilario
Decision tree learning algorithms produce accurate models that can be interpreted by domain experts. However, these algorithms are known to be unstable – they can produce drastic...