In 2015 joined as a Research Fellow the Visual Information Laboratory
, led by Prof David R. Bull, within the Department of Electrical and Electronic Engineering, University of Bristol, UK.
I received my Ph.D. in July 2014 from the Department of Computer Science and Engineering, University of Ioannina, Greece, under the guidance of Prof Lisimachos P. Kondi
My main research interests include topics around the video processing pipeline: acquisition, analysis, compression, and communication, as detailed below. Other side research activities include data and biomedical engineering.
Recent Journal Papers
- Study of Compression Statistics and Prediction of Rate-Distortion Curves for Video Texture [paper]
A. Katsenou, M. Afonso, and D. R. Bull, Signal Processing: Image Communication, vol. 101, 2022.
- Efficient Bitrate Ladder Construction for Content-Optimised Adaptive Video Streaming [paper] [dataset]
A. V. Katsenou, J. Sole, and D. R. Bull, IEEE Open Journal of Signal Processing, vol.2, 2021.
- BVI-SynTex: A Synthetic Video Texture Dataset for Video Compression and Video Quality Assessment [paper] [dataset]
A. Katsenou, G. Dimitrov, D. Ma, and D. R. Bull, IEEE Transactions on Multimedia, vol.23, 2021.
- Feature Selection is Critical for 2-Year Prognosis in Advanced Stage High Grade Serous Ovarian Cancer by Using Machine Learning [paper]
A. Laios, A. Katsenou, Y. Sheng Tan, R. Johnson, M. Otify, A. Kaufmann, S. Munot, A. Thangavelu, R. Hutson, T. Broadhead, G. Theophilou, D. Nugent, and D. De Jong Cancer Control, vol.28, Jan. 2021.
Recent Conference Papers
- VMAF-based Bitrate Ladder Estimation for Adaptive Streaming [paper]
A. V. Katsenou, F. Zhang, K. Swanson, M. Afonso, J. Sole and D. R. Bull, Picture Coding Symposium, Bristol, UK, 2021.
- Enhancing VMAF through New Feature Integration and Model Combination [paper]
F. Zhang, A. V. Katsenou, C. Bampis, L. Krasula, Z. Li, and D. R. Bull, Picture Coding Symposium, Bristol, UK, 2021.
- Feature selection for two-year prognosis in advanced stage high grade serous ovarian cancer using machine learning methods [paper]
A. Laios, A. V. Katsenou, Y. Tan, M. Otify, R. Hutson, A. Kaufmann A, S. Munot, A. Thangavelu, D. De Jong, T. Broadhead, G. Theophilou, D. Nugent, International Journal of Gynecologic Cancer, 2021.
For all papers and datasets see the links below: