Ghent University Academic Bibliography

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Your filters: cql: author="Masala, Enrico" or (type any "bookEditor issueEditor" and editor="Masala, Enrico")

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Predicting individual quality ratings of compressed images through deep CNNs-based artificial observers

Lohic Fotio Tiotsop, Antonio Servetti, Marcus Barkowsky, Peter Pocta, Tomas Mizdos, Glenn Van Wallendael (UGent) and Enrico Masala

(2023) SIGNAL PROCESSING-IMAGE COMMUNICATION. 112.
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- Journal Article
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On the link between subjective score prediction and disagreement of video quality metrics

Lohic Fotio Tiotsop, Florence Agboma, Glenn Van Wallendael (UGent) , Ahmed Aldahdooh, Sebastian Bosse, Lucjan Janowski, Marcus Barkowsky and Enrico Masala

(2021) IEEE ACCESS. 9. p.152923-152937
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Computing quality-of-experience ranges for video quality estimation

Lohic Fotio Tiotsop, Enrico Masala, Ahmed Aldahdooh, Glenn Van Wallendael (UGent) and Marcus Barkowsky

(2019) 2019 ELEVENTH INTERNATIONAL CONFERENCE ON QUALITY OF MULTIMEDIA EXPERIENCE (QOMEX). In International Workshop on Quality of Multimedia Experience
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Improving relevant subjective testing for validation : comparing machine learning algorithms for finding similarities in VQA datasets using objective measures

Ahmed Aldahdooh, Enrico Masala, Glenn Van Wallendael (UGent) , Peter Lambert (UGent) and Marcus Barkowsky

(2019) SIGNAL PROCESSING-IMAGE COMMUNICATION. 74. p.32-41
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Improved performance measures for video quality assessment algorithms using training and validation sets

Ahmed Aldahdooh, Enrico Masala, Olivier Janssens (UGent) , Glenn Van Wallendael (UGent) , Marcus Barkowsky and Patrick Le Callet

(2019) IEEE TRANSACTIONS ON MULTIMEDIA. 21(8). p.2026-2041

Academic Bibliography

Predicting individual quality ratings of compressed images through deep CNNs-based artificial observers

On the link between subjective score prediction and disagreement of video quality metrics

Computing quality-of-experience ranges for video quality estimation

Improving relevant subjective testing for validation : comparing machine learning algorithms for finding similarities in VQA datasets using objective measures

Improved performance measures for video quality assessment algorithms using training and validation sets

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