Visual Quality Assessment by Machine Learning

This book delves into the innovative world of visual quality assessment through the lens of machine learning. It explores the emerging techniques that blend computer vision and artificial intelligence to evaluate visual content's quality effectively. The author presents a comprehensive examination of algorithms and methodologies that can enhance the accuracy of quality assessment in various applications, from digital images to video streaming.

With a focus on practical implementations, the book provides insights into how machine learning models can be trained and deployed to analyze visual data. It aims to equip engineers and researchers with the tools necessary to improve visual quality in numerous fields, including telecommunications and multimedia. Readers will find valuable information that bridges the gap between theoretical concepts and real-world applications in visual quality assessment.