Predicting Single Observer's Votes from Objective Measures using Neural Networks. - Lohic Fotio Tiotsop; Tomas Mizdos; Miroslav Uhrina; Peter Pocta; Marcus Barkowsky; Enrico Masala (HVEI, 2020)

QoE on H.264 and H.265: Crowdsourcing versus Laboratory Testing. - Miroslav Uhrina; Juraj Bienik; Tomas Mizdos (RADIOELEKTRONIKA, 2020)

How to Train No Reference Video Quality Measures for New Coding Standards using Existing Annotated Datasets? - Lohic Fotio Tiotsop; Tomas Mizdos; Enrico Masala; Marcus Barkowsky; Peter Pocta (MMSP, 2021)

How to reuse existing annotated image quality datasets to enlarge available training data with new distortion types. - Tomas Mizdos; Marcus Barkowsky; Miroslav Uhrina; Peter Pocta (Multim. Tools Appl., 2021)

Modeling and estimating the subjects' diversity of opinions in video quality assessment: a neural network based approach. - Lohic Fotio Tiotsop; Tomas Mizdos; Miroslav Uhrina; Marcus Barkowsky; Peter Pocta; Enrico Masala (Multim. Tools Appl., 2021)

Mimicking Individual Media Quality Perception with Neural Network based Artificial Observers. - Lohic Fotio Tiotsop; Tomas Mizdos; Marcus Barkowsky; Peter Pocta; Antonio Servetti; Enrico Masala (ACM Trans. Multim. Comput. Commun. Appl., 2022)

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; Enrico Masala (Signal Process. Image Commun., 2023)