Soft Computing Approach to Pattern Recognition and Image ProcessingAshish Ghosh, Sankar K. Pal This volume provides a collection of sixteen articles containing review and new material. In a unified way, they describe the recent development of theories and methodologies in pattern recognition, image processing and vision using fuzzy logic, artificial neural networks, genetic algorithms, rough sets and wavelets with significant real life applications.The book details the theory of granular computing and the role of a rough-neuro approach as a way of computing with words and designing intelligent recognition systems. It also demonstrates applications of the soft computing paradigm to case based reasoning, data mining and bio-informatics with a scope for future research.The contributors from around the world present a balanced mixture of current theory, algorithms and applications, making the book an extremely useful resource for students and researchers alike. |
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Soft Computing Approach to Pattern Recognition and Image Processing Ashish Ghosh,Sankar K. Pal Limited preview - 2002 |
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AANN models adaptation rules analysis aposteriori applications approach approximate beta sheet case-base CBR system chapter chromosome classifier clustering algorithm coefficients combination components compression constructed correlation corresponding crossover data mining data set decision tree defined denoted distribution encoder ensemble equation error example extraction feature vectors Fourier spectrum frame fusion fuzzy rule fuzzy set gene genetic algorithms Ghosh granular computing granular world hyperplanes IEEE Transactions image processing input k-means algorithm learning linear macroblock measure membership functions method motion estimation motion vector multi-objective mutation neural network neurons node nonlinear object obtained operator optimization output layer parameters partition pattern recognition tasks performance pixels Polkowski problem Proc protein rate control represent representation residue rough set samples scheme Section segmentation shot shown in Fig Skowron soft computing solution space speaker recognition structure techniques tion training data transformation video sequences weights Yegnanarayana