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Record Nr. |
UNINA9910299491503321 |
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Titolo |
Support Vector Machines Applications / / edited by Yunqian Ma, Guodong Guo |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014 |
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ISBN |
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Edizione |
[1st ed. 2014.] |
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Descrizione fisica |
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1 online resource (306 p.) |
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Disciplina |
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Soggetti |
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Signal processing |
Image processing |
Speech processing systems |
Computer communication systems |
Computational complexity |
Computational intelligence |
Computer organization |
Electrical engineering |
Signal, Image and Speech Processing |
Computer Communication Networks |
Complexity |
Computational Intelligence |
Computer Systems Organization and Communication Networks |
Communications Engineering, Networks |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters. |
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Nota di contenuto |
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Augmented-SVM for gradient observations with application to learning multiple-attractor dynamics -- Multi-class Support Vector Machine -- Novel Inductive and Transductive Transfer Learning Approaches Based on Support Vector Learning -- Security Evaluation of Support Vector Machines in Adversarial Environments -- Application of SVMs to the |
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Bag-of-features Model— A Kernel Perspective -- Support Vector Machines for Neuroimage Analysis: Interpretation from Discrimination -- Kernel Machines for Imbalanced Data Problem and the Use in Biomedical Applications -- Soft Biometrics from Face Images using Support Vector Machines. |
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Sommario/riassunto |
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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. |
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