Covers PAC model, decision tree, Bayesian learning, and support vector machines for foundational knowledge
Introduces advanced topics such as Adaboost, compressive sensing, and deep learning for modern applications
Explores classifier design, face recognition, time series recognition, image classification, and object detection for practical use
Written by experts from Beihang University and Nana Lin for authoritative content
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Report copyright infringement by Baochang Zhang (Author), Ce Li (Author), Nana Lin (Author)
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 int