TY - BOOK ID - 4869506 TI - Visual Quality Assessment by Machine Learning AU - Xu, Long. AU - Lin, Weisi. AU - Kuo, C.-C. Jay. PY - 2015 SN - 9789812874689 9812874674 9789812874672 9812874682 PB - Singapore : Springer Singapore : Imprint: Springer, DB - UniCat KW - Engineering. KW - Signal, Image and Speech Processing. KW - Image Processing and Computer Vision. KW - Computational Intelligence. KW - Computer vision. KW - Ingénierie KW - Vision par ordinateur KW - Engineering & Applied Sciences KW - Electrical & Computer Engineering KW - Telecommunications KW - Electrical Engineering KW - Applied Physics KW - Image processing. KW - Computational intelligence. KW - Intelligence, Computational KW - Artificial intelligence KW - Soft computing KW - Pictorial data processing KW - Picture processing KW - Processing, Image KW - Imaging systems KW - Optical data processing KW - Construction KW - Industrial arts KW - Technology KW - Machine vision KW - Vision, Computer KW - Image processing KW - Pattern recognition systems KW - Signal processing. KW - Speech processing systems. KW - Optical data processing. KW - Optical computing KW - Visual data processing KW - Bionics KW - Electronic data processing KW - Integrated optics KW - Photonics KW - Computers KW - Computational linguistics KW - Electronic systems KW - Information theory KW - Modulation theory KW - Oral communication KW - Speech KW - Telecommunication KW - Singing voice synthesizers KW - Processing, Signal KW - Information measurement KW - Signal theory (Telecommunication) KW - Optical equipment KW - Machine learning. KW - Digital techniques. KW - Digital image processing KW - Digital electronics KW - Learning, Machine KW - Machine theory UR - https://www.unicat.be/uniCat?func=search&query=sysid:4869506 AB - 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. ER -