Machine Learning and Visual Perception / / Baochang Zhang.

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 p...

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Superior document:Title is part of eBook package: De Gruyter DG Ebook Package English 2020
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Place / Publishing House:Berlin ;, Boston : : De Gruyter, , [2020]
©2020
Year of Publication:2020
Language:English
Series:De Gruyter Textbook
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Physical Description:1 online resource (X, 142 p.)
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245 1 0 |a Machine Learning and Visual Perception /  |c Baochang Zhang. 
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505 0 0 |t Frontmatter --   |t Contents --   |t Introduction --   |t 1. Introduction of machine learning --   |t 2. PAC Model --   |t 3. Decision tree learning --   |t 4. Bayesian learning --   |t 5. Support vector machines --   |t 6. AdaBoost --   |t 7. Compressed sensing --   |t 8. Subspace learning --   |t 9. Deep learning and neural networks --   |t 10. Reinforcement learning --   |t Bibliography --   |t Index 
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520 |a 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. 
530 |a Issued also in print. 
538 |a Mode of access: Internet via World Wide Web. 
546 |a In English. 
588 0 |a Description based on online resource; title from PDF title page (publisher's Web site, viewed 27. Jan 2023) 
700 1 |a Tsinghua University Press,   |e contributor.  |4 ctb  |4 https://id.loc.gov/vocabulary/relators/ctb 
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