Machine Learning and Visual Perception

✍ Scribed by Baochang Zhang, Ce Li, Nana Lin

Publisher: De Gruyter
Year: 2020
Tongue: English
Leaves: 152
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Machine Learning and Visual Perception provides an up-to-date overview on the topic, including the PAC model, decision tree, Bayesian learning, support vector machines, AdaBoost, compressive sensing and so on.

Both classic and novel algorithms are introduced in classifier design, face recognition, deep learning, time series recognition, image classification, and object detection.

✦ Table of Contents

Contents
Introduction
1. Introduction of machine learning
2. PAC Model
3. Decision tree learning
4. Bayesian learning
5. Support vector machines
6. AdaBoost
7. Compressed sensing
8. Subspace learning
9. Deep learning and neural networks
10. Reinforcement learning
Bibliography
Index

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