Synopsis
The automated handwritten digit recognition task using supervised learning (classification) has many practical applications such as online handwriting recognition on electronic devices, recognizing postal mail codes for mail sorting, processing bank cheque amounts, and numeric entries in various forms filled manually and so on. Though the task is relatively a simple machine learning task, that is, the input consists of black and white pixels well separated from background which are categorized into output categories but has varied challenges associated.Deep learning can be applied to study multilevel representations of data before proceeding with classification. In the work presented in this book we compare various approaches and their variations to generate an optima set of features which can be used for the classification problem of handwritten digits.
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Handwritten Digit Recognition Using Deep Learning
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LAP LAMBERT Academic Publishing Sep 2017, 2017
ISBN 10: 6202024844
ISBN 13: 9786202024846
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The automated handwritten digit recognition task using supervised learning (classification) has many practical applications such as online handwriting recognition on electronic devices, recognizing postal mail codes for mail sorting, processing bank cheque amounts, and numeric entries in various forms filled manually and so on. Though the task is relatively a simple machine learning task, that is, the input consists of black and white pixels well separated from background which are categorized into output categories but has varied challenges associated.Deep learning can be applied to study multilevel representations of data before proceeding with classification. In the work presented in this book we compare various approaches and their variations to generate an optima set of features which can be used for the classification problem of handwritten digits. 80 pp. Englisch. Seller Inventory # 9786202024846
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Handwritten Digit Recognition Using Deep Learning
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ISBN 13: 9786202024846
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Handwritten Digit Recognition Using Deep Learning
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ISBN 13: 9786202024846
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kumar AkshiAkshi Kumar is a Ph.D in Computer Engineering from the University of Delhi, Delhi, India and currently working as an Assistant Professor in Department of Computer Science & Engineering at the Delhi Technological University. Seller Inventory # 167895803
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Handwritten Digit Recognition Using Deep Learning
Published by
LAP LAMBERT Academic Publishing Sep 2017, 2017
ISBN 10: 6202024844
ISBN 13: 9786202024846
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The automated handwritten digit recognition task using supervised learning (classification) has many practical applications such as online handwriting recognition on electronic devices, recognizing postal mail codes for mail sorting, processing bank cheque amounts, and numeric entries in various forms filled manually and so on. Though the task is relatively a simple machine learning task, that is, the input consists of black and white pixels well separated from background which are categorized into output categories but has varied challenges associated.Deep learning can be applied to study multilevel representations of data before proceeding with classification. In the work presented in this book we compare various approaches and their variations to generate an optima set of features which can be used for the classification problem of handwritten digits.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 80 pp. Englisch. Seller Inventory # 9786202024846
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Handwritten Digit Recognition Using Deep Learning
Published by
LAP LAMBERT Academic Publishing, 2017
ISBN 10: 6202024844
ISBN 13: 9786202024846
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The automated handwritten digit recognition task using supervised learning (classification) has many practical applications such as online handwriting recognition on electronic devices, recognizing postal mail codes for mail sorting, processing bank cheque amounts, and numeric entries in various forms filled manually and so on. Though the task is relatively a simple machine learning task, that is, the input consists of black and white pixels well separated from background which are categorized into output categories but has varied challenges associated.Deep learning can be applied to study multilevel representations of data before proceeding with classification. In the work presented in this book we compare various approaches and their variations to generate an optima set of features which can be used for the classification problem of handwritten digits. Seller Inventory # 9786202024846
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Handwritten Digit Recognition Using Deep Learning
Published by
LAP LAMBERT Academic Publishing, 2017
ISBN 10: 6202024844
ISBN 13: 9786202024846
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