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Machine Learning in Computer Vision

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Cover of 'Machine Learning in Computer Vision'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Theory: Probabilistic Classifiers
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    Chapter 3 Theory: Generalization Bounds
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    Chapter 4 Theory: Semi-Supervised Learning
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    Chapter 5 Algorithm: Maximum Likelihood Minimum Entropy HMM
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    Chapter 6 Algorithm: Margin Distribution Optimization
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    Chapter 7 Algorithm: Learning the Structure of Bayesian Network Classifiers
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    Chapter 8 Application: Office Activity Recognition
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    Chapter 9 Application: Multimodal Event Detection
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    Chapter 10 Application: Facial Expression Recognition
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    Chapter 11 Application: Bayesian Network Classifiers for Face Detection
Attention for Chapter 2: Theory: Probabilistic Classifiers
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