Application Neural Networks Learning (25 results)

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Published by Independently published 2019-10-10, 2019
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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.

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Condition: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.

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Hardcover. Condition: gut. 2001. Application of Neural Networks and Other Learning Technologies in Process Engineering In englischer Sprache. pages.

Language: English
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paperback. Condition: New. Language:Chinese.Paperback. Pub Date: 2023-09 Pages: 284 Publisher: Water Resources and Hydropower Press This book starts with the history of the development of artificial intelligence. gradually goes into the framework structure of neural networks and the principles of algorithm optimization. and fina…lly demonstrates the specific workflow of neural networks in actual combat through classic cases. allowing readers to deeply understand the core characteristics and usage of deep learning throug.

Published by Independently Published Okt 2019, 2019
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- Softcover
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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.