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Book Description Condition: New. Seller Inventory # ABLIING23Mar3113020186709
Book Description PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # L0-9783639082593
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Book Description Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The increasing demand for enhanced security in the daily life has directed the improvement of the reliable and intelligent personal identification system based on biometrics. Iris recognition has been regarded as one of the most reliable biometrics technologies in recent years. In this book, an iris recognition scheme is presented as a biometrically based technology for person identification using Multi-Class Support Vector Machines (SVM). The Multi-Objectives Genetic Algorithms (MOGA) is used to select the most significant features in order to increase the matching accuracy. The traditional SVM is modified into an asymmetrical SVM to treat the cases of False Accept and False Reject differently and also to control the unbalanced data of a specific class with respect to the other classes. In order to improve the generalization performance of SVM, the optimal values of SVM parameters are selected. The experimental results indicate that the proposed iris recognition scheme can be applied to a wide range of security-related application areas with an encouraging recognition rate. 156 pp. Englisch. Seller Inventory # 9783639082593
Book Description Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The increasing demand for enhanced security in the daily life has directed the improvement of the reliable and intelligent personal identification system based on biometrics. Iris recognition has been regarded as one of the most reliable biometrics technologies in recent years. In this book, an iris recognition scheme is presented as a biometrically based technology for person identification using Multi-Class Support Vector Machines (SVM). The Multi-Objectives Genetic Algorithms (MOGA) is used to select the most significant features in order to increase the matching accuracy. The traditional SVM is modified into an asymmetrical SVM to treat the cases of False Accept and False Reject differently and also to control the unbalanced data of a specific class with respect to the other classes. In order to improve the generalization performance of SVM, the optimal values of SVM parameters are selected. The experimental results indicate that the proposed iris recognition scheme can be applied to a wide range of security-related application areas with an encouraging recognition rate. Seller Inventory # 9783639082593
Book Description PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # L0-9783639082593
Book Description Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The increasing demand for enhanced security in the daily life has directed the improvement of the reliable and intelligent personal identification system based on biometrics. Iris recognition has been regarded as one of the most reli. Seller Inventory # 4955788