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Neural Networks, Machine Learning, and Image Processing
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Neural Networks, Machine Learning, and Image Processing : Mathematical Modeling and Applications

Book Details

Format Paperback / Softback
ISBN-10 1032300167
ISBN-13 9781032300160
Publisher Taylor & Francis Ltd
Imprint CRC Press
Country of Manufacture GB
Country of Publication GB
Publication Date Dec 19th, 2024
Print length 202 Pages
Weight 453 grams
Ksh 8,800.00
Werezi Extended Catalogue 0 in stock

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The text presents mathematical modeling techniques such as wavelet transform, differential calculus, and numerical techniques for multi-dimensional data. It will serve as an ideal reference text for graduate students and academic researchers in diverse engineering fields such as electrical, electronics and communication, and computer.

The text comprehensively discusses the latest mathematical modelling techniques and their applications in various areas such as fuzzy modelling, signal processing, neural network, machine learning, image processing, and their numerical analysis. It further covers image processing techniques like Viola-Jones Method for face detection and fuzzy approach for person video emotion. It will serve as an ideal reference text for graduate students and academic researchers in the fields of mechanical engineering, electronics, communication engineering, computer engineering, and mathematics.

This book:

  • Discusses applications of neural networks, machine learning, image processing, and mathematical modeling.
  • Provides simulations techniques in machine learning and image processing-based problems.
  • Highlights artificial intelligence and machine learning techniques in the detection of diseases.
  • Introduces mathematical modeling techniques such as wavelet transform, modeling using differential equations, and numerical techniques for multi-dimensional data.
  • Includes real-life problems for better understanding.

The book presents mathematical modeling techniques such as wavelet transform, differential equations, and numerical techniques for multi-dimensional data. It will serve as an ideal reference text for graduate students and academic researchers in diverse engineering fields such as mechanical, electronics and communication and computer.


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