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Deep neural network–based enhancement for image and video streaming systems: A survey and future directions
Internet-enabled smartphones and ultra-wide displays are transforming a variety of visual
apps spanning from on-demand movies and 360° videos to video-conferencing and live …
apps spanning from on-demand movies and 360° videos to video-conferencing and live …
Loki: improving long tail performance of learning-based real-time video adaptation by fusing rule-based models
Maximizing the quality of experience (QoE) for real-time video is a long-standing challenge.
Traditional video transport protocols, represented by a few deterministic rules, can hardly …
Traditional video transport protocols, represented by a few deterministic rules, can hardly …
Learning tailored adaptive bitrate algorithms to heterogeneous network conditions: A domain-specific priors and meta-reinforcement learning approach
Internet adaptive video streaming is a typical form of video delivery that leverages adaptive
bitrate (ABR) algorithms to provide video services with high quality of experience (QoE) for …
bitrate (ABR) algorithms to provide video services with high quality of experience (QoE) for …
Deep reinforcement learning with communication transformer for adaptive live streaming in wireless edge networks
The emerging mobile edge computing (MEC) technology has been recently applied to
improve the Quality of Experience (QoE) of network services, such as live video streaming …
improve the Quality of Experience (QoE) of network services, such as live video streaming …
A workload-aware DVFS robust to concurrent tasks for mobile devices
Power governing is a critical component of modern mobile devices, reducing heat
generation and extending device battery life. A popular technology of power governing is …
generation and extending device battery life. A popular technology of power governing is …
{GRACE}:{Loss-Resilient}{Real-Time} video through neural codecs
In real-time video communication, retransmitting lost packets over high-latency networks is
not viable due to strict latency requirements. To counter packet losses without …
not viable due to strict latency requirements. To counter packet losses without …
HCFL: A high compression approach for communication-efficient federated learning in very large scale IoT networks
Federated learning (FL) is a new artificial intelligence concept that enables Internet-of-
Things (IoT) devices to learn a collaborative model without sending the raw data to …
Things (IoT) devices to learn a collaborative model without sending the raw data to …
BoB: Bandwidth prediction for real-time communications using heuristic and reinforcement learning
Bandwidth prediction is critical in any Real-time Communication (RTC) service or
application. This component decides how much media data can be sent in real time …
application. This component decides how much media data can be sent in real time …
Cloud-edge learning for adaptive video streaming in B5G internet-of-thing systems
The development of Internet of Things (IoT) networks causes an increasing demand for high-
quality video streaming, which results in the burden of traditional mobile cloud computing …
quality video streaming, which results in the burden of traditional mobile cloud computing …
Artificial intelligence of things: A survey
The integration of the Internet of Things (IoT) and modern Artificial Intelligence (AI) has given
rise to a new paradigm known as the Artificial Intelligence of Things (AIoT). In this survey, we …
rise to a new paradigm known as the Artificial Intelligence of Things (AIoT). In this survey, we …