| 書(shū)目名稱(chēng) | Visual Quality Assessment by Machine Learning |
| 編輯 | Long Xu,Weisi Lin,C.-C. Jay Kuo |
| 視頻video | http://file.papertrans.cn/984/983774/983774.mp4 |
| 概述 | Presents the emerging techniques of learning based visual quality assessment.Highlights machine learning techniques and their applications in visual quality assessment.Includes a number of real-world |
| 叢書(shū)名稱(chēng) | SpringerBriefs in Electrical and Computer Engineering |
| 圖書(shū)封面 |  |
| 描述 | The book encompasses the state-of-the-art visual quality assessment (VQA) and learning based visual quality assessment (LB-VQA) by providing a comprehensive overview of the existing relevant methods. It delivers the readers the basic knowledge, systematic overview and new development of VQA. It also encompasses the preliminary knowledge of Machine Learning (ML) to VQA tasks and newly developed ML techniques for the purpose. Hence, firstly, it is particularly helpful to the beginner-readers (including research students) to enter into VQA field in general and LB-VQA one in particular. Secondly, new development in VQA and LB-VQA particularly are detailed in this book, which will give peer researchers and engineers new insights in VQA. |
| 出版日期 | Book 2015 |
| 關(guān)鍵詞 | Feature Selection; Machine Learning; Rank Learning; Support Vector Learning; Visual Quality Assessment ( |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-981-287-468-9 |
| isbn_softcover | 978-981-287-467-2 |
| isbn_ebook | 978-981-287-468-9Series ISSN 2191-8112 Series E-ISSN 2191-8120 |
| issn_series | 2191-8112 |
| copyright | The Author(s) 2015 |
|Archiver|手機(jī)版|小黑屋|
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