Soft computing approach to pattern recognition and image processing
Author(s)
Bibliographic Information
Soft computing approach to pattern recognition and image processing
（Series in machine perception and artificial intelligence / editors, H. Bunke, P.S.P. Wang, v. 53）
World Scientific, c2002
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
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.
Table of Contents
- Part I: multiple classifier systems, J. Kittler
- building decision trees from the Fourier spectrum of a tree ensemble, H. Kargupta
- clustering large data sets, M.N. Murty
- multi-objective variable string genetic classifier - application to remote sensing imagery, S. Bandyopadhyay et al. Part II: dissimilarity measures between fuzzy sets or fuzzy structures, K.R. Bhutani and A. Rosenfeld
- early vision -concepts and algorithms, V.D. Gesu
- self-organizing neural network for multi-level image segmentation, A. Ghosh and A. Sen
- geometric transformation by moment method with wavelet matrix, Y.Y. Tang et al
- new computationally efficient algorithms for video coding, T. Acharya and H.M. Kim
- soft computing for computational media aesthetics - analyzing video content for meaning, S. Chaudhury et al. Part III: towards granular multi-agent systems, A. Skowron
- granular computing and pattern recognition, W. Pedrycz
- case base maintenance - a soft computing perspective, S.C.K. Shiu. Part IV: autoassociative neural network models for pattern recognition tasks in speech and image, B. Yegnanarayana et al
- protein structure prediction using soft computing, S. Mitra et al
- pattern classification for biological data mining, S.B. Cho.
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