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Focus on current developments in the field of Support Vector Machines
Illustrates critical applications of support vector machines to important real world problems
Provides critical review of the state-of-the-art techniques on SVM, such as domain transfer SVM, object recognition, soft biometrics, and biomedical applications
Support vector machines (SVM) have both a solid mathematical background and good performance in practical applications. This book focuses on the recent advances and applications of the SVM in different areas, such as image processing, medical practice, computer vision, pattern recognition, machine learning, applied statistics, business intelligence, and artificial intelligence. The aim of this book is to create a comprehensive source on support vector machine applications, especially some recent advances.
Content Level »Research
Keywords »Business Intelligence - Computer Vision - Kernel Machines - Large Margin Classifier - Learning in the Small Sample Case - Learning with High Dimensionality - Machine Learning - Pattern Recognition - Support Vector Machine