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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Artificial Neural Networks Applied to Digital Images with MATLAB Code

Artificial Neural Networks Applied to Digital Images with MATLAB Code

Othman a. Khfagy, Muhammad Atta

Paperback

General Computers

ISBN10: 6209788807
ISBN13: 9786209788802
Publisher: LAP Lambert Academic Publishing
Published: Mar 26 2026
Pages: 152
Weight: 0.47
Height: 0.35 Width: 6.00 Depth: 9.00
Language: English
Artificial 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.

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