Ghent University Academic Bibliography

Show Sort by

Your filters: cql: author="Barkowsky, Marcus" or (type any "bookEditor journalEditor issueEditor" and editor="Barkow...

Add to list
- Journal Article
- A1
- open access
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
Add to list
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
Add to list
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
Add to list
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
Add to list
- Journal Article
- A1
- open access
Framework for reproducible objective video quality research with case study on PSNR implementations

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

(2018) DIGITAL SIGNAL PROCESSING. 77. p.195-206
Add to list
- Journal Article
- A1
- open access
Reproducible research framework for objective video quality measures using a large-scale database approach

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

(2018) SOFTWAREX. 8. p.64-68
Add to list
- Conference Paper
- P1
- open access
Comparing temporal behavior of fast objective video quality measures on a large-scale database

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

(2016) 2016 Picture Coding symposium (PCS). In Picture Coding Symposium
Add to list
- Conference Paper
- P1
- open access
Comparing simple video quality measures for loss-impaired video sequences on a large-scale database

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

(2016) 2016 EIGHTH INTERNATIONAL CONFERENCE ON QUALITY OF MULTIMEDIA EXPERIENCE (QOMEX). p.1-6
Add to list
- Conference Paper
- C1
- open access
Full-HD HEVC-encoded video quality assessment database

Glenn Van Wallendael (UGent) , Nicolas Staelens (UGent) , Enrico Masala and Marcus Barkowsky

(2015) 9th International Workshop on Video Processing and Quality Metrics for Consumer Electronics, Proceedings.
Add to list
Predicting full-reference video quality measures using HEVC bitstream-based no-reference features

Muhammad Shahid, Joanna Panasiuk, Glenn Van Wallendael (UGent) , Marcus Barkowsky and Benny Lövström

(2015) International Workshop on Quality of Multimedia Experience.

Academic Bibliography

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

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

Computing quality-of-experience ranges for video quality estimation

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

Framework for reproducible objective video quality research with case study on PSNR implementations

Reproducible research framework for objective video quality measures using a large-scale database approach

Comparing temporal behavior of fast objective video quality measures on a large-scale database

Comparing simple video quality measures for loss-impaired video sequences on a large-scale database

Full-HD HEVC-encoded video quality assessment database

Predicting full-reference video quality measures using HEVC bitstream-based no-reference features

Contents

Support

Contact