Neural Networks, Machine Learning, and Image Processing (e-bog) af -
Merigo, Jose M (redaktør)

Neural Networks, Machine Learning, and Image Processing e-bog

436,85 DKK (inkl. moms 546,06 DKK)
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 ...
E-bog 436,85 DKK
Forfattere Merigo, Jose M (redaktør)
Forlag CRC Press
Udgivet 15 december 2022
Længde 202 sider
Genrer Engineering: general
Sprog English
Format pdf
Beskyttelse LCP
ISBN 9781000814293
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.