TY  - BOOK
AU  - Zharkova,Valentina
AU  - Jain,Lakhmi C.
ED  - SpringerLink (Online service)
TI  - Artificial Intelligence in Recognition and Classification of Astrophysical and Medical Images
T2  - Studies in Computational Intelligence,
SN  - 9783540475187
AV  - TA329-348 
U1  - 519 23
PY  - 2007///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg
KW  - Engineering
KW  - Artificial intelligence
KW  - Engineering mathematics
KW  - Appl.Mathematics/Computational Methods of Engineering
KW  - Artificial Intelligence (incl. Robotics)
N1  - to Pattern Recognition and Classification in Medical and Astrophysical Images -- Image Standardization and Enhancement -- Intensity and Region-Based Feature Recognition in Solar Images -- Advanced Feature Recognition and Classification Using Artificial Intelligence Paradigms -- Feature Recognition and Classification Using Spectral Methods
N2  - This book presents innovative techniques in Recognition and Classification of Astrophysical and Medical Images. The contents include: Introduction to pattern recognition and classification in astrophysical and medical images. Image standardization and enhancement. Region-based methods for pattern recognition in medical and astrophysical images. Advanced information processing using statistical methods. Feature recognition and classification using spectral method The book is intended for astrophysicists, medical researches, engineers, research students and technically aware managers in the Universities, Astrophysical Observatories, Medical Research Centres working on the processing of large archives of astrophysical or medical digital images. This book can be used as a text book for students of Computing, Cybernetics, Applied Mathematics and Astrophysics. While there are plenty of volumes tackling pattern recognition problems in finance, marketing, and the like, I commend the editors and the authors for their efforts to tackle the big questions in life, and their excellent contributions to this book. Professor Kate Smith-Miles Head, School of Engineering and Information Technology, Deakin University, Australia
UR  - http://dx.doi.org/10.1007/978-3-540-47518-7
ER  -