Video Compression and Optimization Technologies - Review

The use of video streaming is constantly increasing. High-resolution video requires resources on both the sender and the receiver side. There are many compression techniques that can be utilized to compress the video and simultaneously maintain quality. The main goal of this paper is to provide an overview of video streaming and QoE. This paper describes the basic concepts and discusses existing methodologies to measure QoE. Subjective, objective, and video compression technologies are discussed. This review paper gathers the codec implementation developed by MPEG, Google, and Apple. This paper outlines the challenges and future research directions that should be considered in the measurement and assessment of quality of experience for video services

AI in Medical Imaging Informatics: Current Challenges and Future Directions

This paper reviews state-of-the-art research solutions across the spectrum of medical imaging informatics, discusses clinical translation, and provides future directions for advancing clinical practice. More specifically, it summarizes advances in medical imaging acquisition technologies for different modalities, highlighting the necessity for efficient medical data management strategies in the context of AI in big healthcare data analytics. It then provides a synopsis of contemporary and emerging algorithmic methods for disease classification and organ/ tissue segmentation, focusing on AI and deep learning architectures that have already become the de facto approach. The clinical benefits of in-silico modelling advances linked with evolving 3D reconstruction and visualization applications are further documented. Concluding, integrative analytics approaches driven by associate research branches highlighted in this study promise to revolutionize imaging informatics as known today across the healthcare continuum for both radiology and digital pathology applications. The latter, is projected to enable informed, more accurate diagnosis, timely prognosis, and effective treatment planning, underpinning precision medicine

Video-assisted Overtaking System enabled by V2V Communications

V2X (Vehicle-to-Everything) is a promising technology to diminish road hazards and increase driving safety. This thesis focuses in the transmission of video between vehicles (V2V, Vehicle-to-Vehicle) in an overtaking situation, helping drivers to be more aware and less error-prone in these situations. In the implementation, the vehicle reads from vehicle's CAN and GPS data to setup the system, streams his Line of Sight to the overtaking vehicle and uses DSRC as the communication technology