Probabilistic self-organizing maps for continuous data
IEEE Transactions on Neural Networks
Robust object segmentation using genetic optimization of morphological processing chains
SSIP'05 Proceedings of the 5th WSEAS international conference on Signal, speech and image processing
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From the Publisher:This book is devoted to two interrelated techniques in solving some important problems in machine intelligence and pattern recognition, namely probabilistic reasoning and computational learning. It is divided into four parts, the first of which describes several new inductive principles and techniques used in computational learning. The second part contains papers on Bayesian and Causal Belief networks. Part three includes chapters on case studies and descriptions of several hybrid systems and the final part describes some related theoretical work in the field of probabilistic reasoning.