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Interactive Demonstrations of the Locally Adaptive Fusion For Combining Objective Quality Measures Host Publication: IEEE International Conference on Image Processing (ICIP 2014) Authors: A. Barri, A. Dooms and P. Schelkens Publisher: IEEE Publication Date: Oct. 2014 ISBN: 978-1-4799-5751-4
Abstract: To automate quality monitoring of multimedia applications,
objective quality measures for images and video content need
to be designed. Objective quality measures that model the
Human Visual System (HVS) have a disappointing performance,
because the HVS is not sufficiently understood. Integrating
machine learning (ML) techniques may increase the performance.
Unfortunately, traditional ML is difficult to interpret.
To this end, we developed the Locally Adaptive Fusion (LAF),
for more flexible and reliable quality predictions. This
manuscript proposes six interactive programs and a website
that demonstrate the effectiveness of LAF, which complement
the technical focus of the corresponding journal paper.
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