Dr. Artusi work interests lays in the fields of image/video processing, computer vision and deep-learning deploying an innovative solution for current computer vision applications through a smarter imaging/video pipeline. He is one of the major contributors and editors of the new ISO/IEC/18477-JPEG-XT standard, as member of the IST/037 coding of picture, audio, multimedia and hypermedia information, of the British Standard Institute (BSI), ISO/IEC/SC29/WG1/JPEG and ISO/IEC/SC29/WG11/MPEG standardization committee’s. For these activities he has been recognized with the prestigious BSI Emerging Standards Maker Award. He is the co-author of the CRC Press reference book on High Dynamic Range Technology ‘Advanced High Dynamic Range Technology: Theory and Practice’ 1st and 2nd edition and the author of CRC Press book ‘Image Content Retargeting: Maintaining Tone, Color and Spatial Consistency’.

Dr. Milidonis is a Senior Research Associate in the DeepCamera multidisciplinary research group (MRG) at CYENS Centre of Excellence. He received a BSc in Physics from the University of Cyprus (2011), an MSc in Physics and Computing in Medicine and Biology (Medical Physics) from the University of Manchester (2012), and a PhD in Molecular and Clinical Medicine (Neuroimaging) from the University of Edinburgh (2017). Since then, he worked as a post-doctoral Research Associate at the School of Biomedical Engineering & Imaging Sciences, King’s College London, focusing on the fabrication of multimodality physical standards for the assessment and validation of dynamic cardiac first-pass perfusion imaging, as well as the development of algorithms for the automated quantitative analysis of magnetic resonance imaging data. Currently, he works towards the development of deep learning-based tools for image processing, visualization and evaluation, while co-managing the DeepCamera MRG. He is also a registered Medical Physicist in Cyprus, a Consultant Scientist for General Electric Healthcare, UK, and a Visiting Research Associate at King’s College London.

Andreas Loizou is currently working as a Research Associate and Computer Vision Engineer at CYENS Centre of Excellence in the DeepCamera group. He is a holder of an MSc degree in Artificial Intelligence and Adaptive Systems from the University of Sussex (2022), and a BSc degree in Computer Science from the University of Cyprus (2021). His MSc thesis topic was in Ethical Facial Emotion Recognition using Continuous Learning. He has proven experience of couple of years in the field of Computer Vision using deep learning approaches. He has been developing object detection and tracking technologies making use of deep-learning architecture, adapting them to the specific aims and goals of the application. During this period, he has improved the computational complexity of the architecture, developed different training strategies for improving quality performances, as well as investigated different types of loss functions. Improvements in computational complexity have provided an easy deployment into an existing embedded system reducing the prediction latency.