Handwritten Digit Recognition Using by Kumar Akshi (7 results)
- Softcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
Contact seller5-star sellerCondition: New
£ 43.38
£ 10.00 shippingShips from United Kingdom to U.S.A.Quantity: 1 available
Paperback. Condition: Brand New. 80 pages. 8.66x5.91x0.19 inches. In Stock.
- Softcover
Seller: preigu, Osnabrück, Germanypreigu
Contact seller5-star sellerCondition: New
£ 23.18
£ 59.79 shippingShips from Germany to U.S.A.Quantity: 5 available
Taschenbuch. Condition: Neu. Handwritten Digit Recognition Using Deep Learning | Akshi Kumar | Taschenbuch | 80 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9786202024846 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
- Softcover
Seller: Mispah books, Redhill, SURRE, United KingdomMispah books
Contact seller4-star sellerCondition: New
£ 104.00
£ 25.00 shippingShips from United Kingdom to U.S.A.Quantity: 1 available
paperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Language: English
Published by LAP LAMBERT Academic Publishing Sep 2017, 2017
- Softcover
- Print on Demand
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
Contact seller5-star sellerCondition: New
£ 25.43
£ 19.64 shippingShips from Germany to U.S.A.Quantity: 2 available
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.
- Softcover
- Print on Demand
Seller: moluna, Greven, Germanymoluna
Contact seller5-star sellerCondition: New
£ 22.92
£ 41.84 shippingShips from Germany to U.S.A.Quantity: Over 20 available
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.
Language: English
Published by LAP LAMBERT Academic Publishing Sep 2017, 2017
- Softcover
- Print on Demand
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
Contact seller5-star sellerCondition: New
£ 25.43
£ 51.24 shippingShips from Germany to U.S.A.Quantity: 1 available
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, pr…ocessing 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.
- Softcover
- Print on Demand
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
Contact seller5-star sellerCondition: New
£ 27.03
£ 51.83 shippingShips from Germany to U.S.A.Quantity: 1 available
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, pro…cessing 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.
