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Introduction of the school : Soft computing is a consortium of methodologies which work synergetically and provides in one form or another flexible information processing capabilities for handling real life ambiguous situations. Its aim is to exploit the tolerance for imprecision, uncertainty, approximate reasoning, and partial truth in order to achieve tractability, robustness, low cost solution and close resemblance with human like decision making.  The relevance of soft computing for pattern recognition and image processing is already established during the last few years.  The subject has recently matured because of its potential applications in problems like remotely sensed data analysis, data mining, web mining, global positioning systems, medical imaging, forensic applications, optical character recognition, signature verification, multimedia, target recognition, face recognition and man machine communication. 

Objective of the school :  The objective of this international  school is to provide an opportunity to the researchers, students, teachers and R & D personnel   to be acquainted with the emerging soft computing techniques of machine intelligence starting from introduction to recent advanced  topics with various real life applications. Particular attention will be given on applying these tools to various pattern recognition/ image processing  problems including data mining with speakers from both academia and industry. The school will also give an opportunity to the young researchers to have interaction/establish contacts  with well known senior researchers of the field.

 Course content or broad topics : The course  will cover a balanced mixture of theory and practice including laboratory visits, case studies  and demonstration of industrial products. The theoretical lecture schedule will contain:

introductory  lectures on pattern recognition, image processing  and various soft computing tools such as fuzzy logic, neural networks, genetic algorithms, rough sets;

lectures demonstrating the  different ways of applying these tools to different facets of pattern recognition/image processing  and data mining problems;

lectures on hybridized  methodologies (a combination of two or more soft computing  tools), and their application to the above mentioned tasks ;

lectures  on real life applications such as remotely sensed image analysis, medical image analysis,  target recognition, forensic data analysis,  character recognition etc;

lectures  on advanced topics like soft data mining, soft web mining,  fuzzy logic in internet, rough set theory, granular computing, computational theory of perception etc. with respect to pattern recognition and image processing problems.