Description
Machine Learning Algorithms for Signal and Image Processing is a comprehensive resource that bridges the gap between theoretical machine learning concepts and practical applications in signal and image processing. The book explores fundamental algorithms and advanced techniques used for analyzing, processing, and extracting meaningful information from signals and images.
Written by leading experts including Deepika Ghai, Suman Lata Tripathi, Sobhit Saxena, Manash Chanda, and Mamoun Alazab, this Wiley-IEEE Press publication combines theory with real-world implementations. Readers will gain insights into supervised and unsupervised learning methods, deep learning architectures, and their applications in audio processing, medical imaging, computer vision, and telecommunications. The book includes practical examples, algorithms, and case studies that demonstrate how to solve complex problems in signal and image processing using machine learning approaches.
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