Abstract
In this paper, the idea of adaptive potential active hypercontours (APAH) as a new method of construction of an optimal classifier is presented. The idea of active hypercontours generalizes the traditional active contour methods, which are extensively developed in image analysis, and allows the application of their concepts in other classification tasks. In the presented implementation of APAH the evolution of the potential hypercontour is controlled by simulated annealing algorithm (SA). The method has been evaluated on the IRIS and MNIST databases and compared with traditional classification techniques.
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Tomczyk, A., Szczepaniak, P.S. (2006). Adaptive Potential Active Hypercontours. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2006. ICAISC 2006. Lecture Notes in Computer Science(), vol 4029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11785231_72
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DOI: https://doi.org/10.1007/11785231_72
Publisher Name: Springer, Berlin, Heidelberg
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