Machine Learning for Audio, Image and Video Analysis: Theory and Applications

Camastra, Francesco

Machine Learning for Audio, Image and Video Analysis: Theory and Applications - Heidelberg Springer-Verlag 2008 - 494p

Introduction Part - 1: From Perception to Computation Audio Acquisition, Representation and Storage Image and Video Acquisition, Representation and Storage Part - 2: Machine Learning Bayesian Theory of Decision Clustering Methods Foundations of Statistical Learning Supervised Neural Networks and Ensemble Methods Kernel Methods Markovian Models for Sequential Data Feature Extraction Methods and Manifold Learning Methods Part - 3: Applications Speech and Handwriting Recognition Automatic Face Recognition Video Segmentation and Keyframe Extraction Part - 4: Appendices Statistics Signal Processing Matrix Algebra Mathematical Foundations of Kernel Methods

9781848000063 0.00


Computer Engineering

006.31 / CAM
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