Related papers: Learning from Experience: A Dynamic Closed-Loop Qo…
HTTP Adaptive Streaming (HAS) is nowadays a popular solution for multimedia delivery. The novelty of HAS lies in the possibility of continuously adapting the streaming session to current network conditions, facilitated by Adaptive Bitrate…
Feedback optimization refers to a class of methods that steer a control system to a steady state that solves an optimization problem. Despite tremendous progress on the topic, an important problem remains open: enforcing state constraints…
In real-world vision systems,haze removal is required not only to enhance image visibility but also to meet the specific needs of diverse downstream tasks.To address this challenge,we propose a novel adaptive dynamic dehazing framework that…
This paper aims to propose the quality of experience (QoE) models based on the expectation and/or the perception of 5G users to evaluate for mean opinion score (MOS) for real-time or interactive services/applications with high reliability.…
Consumers of short videos on Internet can have a bad Quality of Experience QoE due to the long distance between the consumers and the servers that hosting the videos. We propose an optimization of the file allocation in telecommunication…
Developing effective approaches to generate enhanced results that align well with human visual preferences for high-quality well-lit images remains a challenge in low-light image enhancement (LLIE). In this paper, we propose a…
In this paper, we present an Android application which is able to evaluate and analyze the perceived Quality of Experience (QoE) for YouTube service in wireless terminals. To achieve this goal, the application carries out measurements of…
The importance of emotions in service and in product design is well known. However, it is still not very well understood how users' emotions can be incorporated in a product or service lifecycle. We argue that this gap is due to a lack of a…
Quality of Experience (QoE) prediction plays a crucial role in optimizing resource management and enhancing user satisfaction across both telecommunication and OTT services. While recent advances predominantly rely on deep learning models,…
Reliable navigation systems have a wide range of applications in robotics and autonomous driving. Current approaches employ an open-loop process that converts sensor inputs directly into actions. However, these open-loop schemes are…
Feedback optimization has emerged as an effective strategy for steady-state optimization of dynamical systems. By exploiting models of the steady-state input-output sensitivity, methods of this type are often sample efficient, and their use…
The rapid uptake of intelligent applications is pushing deep learning (DL) capabilities to Internet-of-Things (IoT). Despite the emergence of new tools for embedding deep neural networks (DNNs) into IoT devices, providing satisfactory…
Adaptive video streaming systems are designed to optimize Quality of Experience (QoE) and, in turn, enhance user satisfaction. However, differences in user profiles and video content lead to different weights for QoE factors, resulting in…
Wireless networks are envisaged to be one of the most important technologies to provide cost-efficient content delivery, including for video applications. They will allow thousands of thousands of fixed and mobile users to access, produce,…
The rate performance of wireless coded caching schemes is typically limited by the lowest achievable per-user rate in the given multicast group, during each transmission time slot. In this paper, we provide a new coded caching scheme,…
This paper aims to improve video streaming by leveraging a simple observation: users are more sensitive to low quality in certain parts of a video than in others. For instance, rebuffering during key moments of a sports video (e.g., before…
Driven by the tremendous technological advancement of personal devices and the prevalence of wireless mobile network accesses, the world has witnessed an explosion in crowdsourced live streaming. Ensuring a better viewers quality of…
Multi-access edge computing (MEC) enables placing video content at the edge of the network aiming to improve the quality of experience (QoE) of the mobile clients. Video content caching at edge servers also reduces traffic in the backhaul…
Continuous QoE prediction is crucial in the purpose of maximizing viewer satisfaction, by which video service providers could improve the revenue. Continuously predicting QoE is challenging since it requires QoE models that are capable of…
Quality of Service (QoS) metrics deal with network quantities, e.g. latency and loss, whereas Quality of Experience (QoE) provides a proxy metric for end-user experience. Many papers in the literature have proposed mappings between various…