Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems: 172 (Studies in Fuzziness and Soft Computing) - Tapa dura

Castillo, Oscar; Melin, Patricia

 
9783540241218: Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems: 172 (Studies in Fuzziness and Soft Computing)

Sinopsis

This monograph describes new methods for intelligent pattern recognition using soft computing techniques including neural networks, fuzzy logic, and genetic algorithms. Hybrid intelligent systems that combine several soft computing techniques are needed due to the complexity of pattern recognition problems. Hybrid intelligent systems can have different architectures, which have an impact on the efficiency and accuracy of pattern recognition systems, to achieve the ultimate goal of pattern recognition. This book also shows results of the application of hybrid intelligent systems to real-world problems of face, fingerprint, and voice recognition. This monograph is intended to be a major reference for scientists and engineers applying new computational and mathematical tools to intelligent pattern recognition and can be also used as a textbook for graduate courses in soft computing, intelligent pattern recognition, computer vision, or applied artificial intelligence.

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Acerca del autor

Dr. Dimitrios Linos has extensive experience in minimally invasive non-endoscopic thyroidectomy (MINET), but he has also introduced the technique of endoscopic and robotic-assisted transaxillary thyroidectomy into Europe. He is Director of Surgery at Hygeia Hospital in Athens, Greece and has a close collaboration with the Department of Endocrine Surgery at Massachusetts General Hospital. He is also Associate Professor at the University of Athens Medical School and Lecturer on Surgery at Harvard Medical School. Dr. Linos is a member of several surgical societies and is actively involved with the American College of Surgeons (ACS), The Society of American Gastrointestinal Endoscopic Surgeons (SAGES), and the International Association of Endocrine Surgeons (IAES). Dr. Woong Youn Chung is a leader in minimally invasive thyroidectomy and has the most extensive experience in robotically assisted transaxillary thyroidectomy. He is staff surgeon and Associate Professor of Surgery at Yonsei University College of Medicine in Seoul Korea. He is Editor-in-chief of the Korean Association of Endocrine Surgeons and an active member in various other professional societies, including the International Association of Endocrine Surgeons (IAES). Dr. Chung has published extensively and is a mentor for several international thyroid surgeons around the world who visit his department and learn the details of robotically assisted thyroidectomy. Dr. Woong Youn Chung is a leader in minimally invasive thyroidectomy and has the most extensive experience in robotically assisted transaxillary thyroidectomy. He is staff surgeon and Associate Professor of Surgery at Yonsei University College of Medicine in Seoul Korea. He is Editor-in-chief of the Korean Association of Endocrine Surgeons and an active member in various other professional societies, including the International Association of Endocrine Surgeons (IAES). Dr. Chung has published extensively and is a mentor for several international thyroid surgeons around the world who visit his department and learn the details of robotically assisted thyroidectomy.

De la contraportada

This monograph describes new methods for intelligent pattern recognition using soft computing techniques including neural networks, fuzzy logic, and genetic algorithms. Hybrid intelligent systems that combine several soft computing techniques are needed due to the complexity of pattern recognition problems. Hybrid intelligent systems can have different architectures, which have an impact on the efficiency and accuracy of pattern recognition systems, to achieve the ultimate goal of pattern recognition. This book also shows results of the application of hybrid intelligent systems to real-world problems of face, fingerprint, and voice recognition. This monograph is intended to be a major reference for scientists and engineers applying new computational and mathematical tools to intelligent pattern recognition and can be also used as a textbook for graduate courses in soft computing, intelligent pattern recognition, computer vision, or applied artificial intelligence.

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Otras ediciones populares con el mismo título

9783642063251: Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems: 172 (Studies in Fuzziness and Soft Computing)

Edición Destacada

ISBN 10:  364206325X ISBN 13:  9783642063251
Editorial: Springer, 2010
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