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Machine Learning for Image Quality Assessment by Cẩm Tú Cầu is a document available to read on EtoBox.

What is Machine Learning for Image Quality Assessment about?

This document discusses machine learning approaches for designing full-reference image quality assessment algorithms. It proposes a method called MLIQM that first classifies image quality using multi-SVM classification according to a 5-point quality scale. It then constructs a feature vector describing image content and performs classification to provide a quality class. Finally, it uses SVM regression to score the quality within the assigned class. The results are compared to classical FR-IQA algorithms to

Author

Cẩm Tú Cầu

Language

EN