Artificial Learning Based Convolution by Bukasa Muepu (10 results)
- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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£ 36.42
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Condition: New. In.
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Seller: preigu, Osnabrück, Germanypreigu
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£ 34.92
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Taschenbuch. Condition: Neu. Artificial learning based on convolution neural networks | Application to the recognition of handwritten digits on bank cheques | Bienvenue Bukasa Muepu (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2025 | Our Knowledge Publishing | EAN 9786208578213 | Verantwortliche Person für die… EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.
- Softcover
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Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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£ 40.71
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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
- Softcover
- Print on Demand
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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£ 38.20
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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.
- Softcover
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
Contact seller5-star sellerCondition: New
£ 38.96
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 64 pp. Englisch.
- Softcover
- Print on Demand
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
Contact seller4-star sellerCondition: New
£ 56.55
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Condition: New. Print on Demand.
- Softcover
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Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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£ 61.48
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Condition: New. Print on Demand.
- Softcover
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Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
Contact seller4-star sellerCondition: New
£ 58.27
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Condition: New. PRINT ON DEMAND.
- Softcover
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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£ 38.96
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Numerical recognition of bank cheques presents a major challenge and plays an important role in today's world, as machines must be able to learn like humans and solve complex problems such as recognizing the digits of bank cheques. Desp…ite attempts to make machines learn like humans, no machine has yet been able to recognize 100% of handwritten digits. Despite attempts to make machines capable of learning like humans, no machine is yet 100% capable of recognizing handwritten digits. It aims to build a prediction model called a classifier that will facilitate this recognition from data in the MNIST database, with a view to possibly helping banks to speed up the processing of banking transactions by cheque.The approach proposed here essentially consists of two steps: feature extraction and classification of image pixels using a convolutional neural network, one of the deep learning algorithms with a proven track record in image processing.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch.
- Softcover
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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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£ 39.57
£ 52.18 shippingShips from Germany to U.S.A.Quantity: 1 available
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Numerical recognition of bank cheques presents a major challenge and plays an important role in today's world, as machines must be able to learn like humans and solve complex problems such as recognizing the digits of bank cheques. Despi…te attempts to make machines learn like humans, no machine has yet been able to recognize 100% of handwritten digits. Despite attempts to make machines capable of learning like humans, no machine is yet 100% capable of recognizing handwritten digits. It aims to build a prediction model called a classifier that will facilitate this recognition from data in the MNIST database, with a view to possibly helping banks to speed up the processing of banking transactions by cheque.The approach proposed here essentially consists of two steps: feature extraction and classification of image pixels using a convolutional neural network, one of the deep learning algorithms with a proven track record in image processing.
