Machine Learning and Visual Perception / Baochang Zhang.
By: Zhang, Baochang [author.]
.
Contributor(s): Tsinghua University Press [contributor.].
Material type: 
BookSeries: De Gruyter Textbook.Publisher: Berlin ; Boston : De Gruyter, [2020]Copyright date: ©2020Description: 1 online resource (X, 142 p.).Content type: text Media type: computer Carrier type: online resourceISBN: 9783110595567.Additional physical formats: No title; No titleOnline resources: Click here to access online | Click here to access online | Cover Issued also in print.Frontmatter -- 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
restricted access online access with authorization star
http://purl.org/coar/access_right/c_16ec
The book provides an up-to-date on machine learning and visual perception, including decision tree, Bayesian learning, support vector machine, AdaBoost, object detection, compressive sensing, deep learning, and reinforcement learning. Both classic and novel algorithms are introduced. With abundant practical examples, it is an essential reference to students, lecturers, professionals, and any interested lay readers.
Issued also in print.
Mode of access: Internet via World Wide Web.
In English.
Description based on online resource; title from PDF title page (publisher's Web site, viewed 27. Jan 2023)
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