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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Online Access: | |
Physical Description: | 1 online resource (X, 142 p.) |
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Other title: | 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 |
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Summary: | 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. |
Format: | Mode of access: Internet via World Wide Web. |
ISBN: | 9783110595567 9783110696288 9783110696271 9783110659061 9783110616859 9783110704716 9783110704518 9783110704815 9783110704617 |
DOI: | 10.1515/9783110595567 |
Access: | restricted access |
Hierarchical level: | Monograph |
Statement of Responsibility: | Baochang Zhang. |