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OverviewArtificial Neural Networks have broad applications in real-world business problems and have been successfully applied across many industries. As they excel at identifying patterns and trends in data, they are well suited for prediction and forecasting tasks such as sales forecasting, industrial process control, customer research, data validation, risk management, and target marketing. This work examines the use of Artificial Neural Networks in the field of image processing. One of the applications studied is edge detection, which significantly reduces data volume and filters out irrelevant information while preserving essential structural features of an image. Edge detection is widely used in various fields, ranging from real-time video surveillance and traffic management to medical imaging. The study presents both entropy-based and neural network-based edge detection methods, specifically using Rényi's entropy and convolutional neural networks, and compares their performance. Full Product DetailsAuthor: Muhammad Atta Othman a KhfagyPublisher: LAP Lambert Academic Publishing Imprint: LAP Lambert Academic Publishing Dimensions: Width: 15.20cm , Height: 0.90cm , Length: 22.90cm Weight: 0.213kg ISBN: 9786209788802ISBN 10: 6209788807 Pages: 152 Publication Date: 26 March 2026 Audience: General/trade , General Format: Paperback Publisher's Status: Active Availability: Available To Order We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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