Please note: In order to keep Hive up to date and provide users with the best features, we are no longer able to fully support Internet Explorer. The site is still available to you, however some sections of the site may appear broken. We would encourage you to move to a more modern browser like Firefox, Edge or Chrome in order to experience the site fully.

Visual Quality Assessment by Machine Learning, PDF eBook

Visual Quality Assessment by Machine Learning PDF

Part of the SpringerBriefs in Electrical and Computer Engineering series

PDF

Please note: eBooks can only be purchased with a UK issued credit card and all our eBooks (ePub and PDF) are DRM protected.

Description

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.

Information

Other Formats

Information

Also in the SpringerBriefs in Electrical and Computer Engineering series  |  View all