Machine Learning for Multimedia Communications

in Special Issue   Posted on December 30, 2020 

Information for the Special Issue

Submission Deadline: Mon 15 Mar 2021
Journal Impact Factor : 3.275
Journal Name : Sensors
Journal Publisher:
Website for the Special Issue:
Journal & Submission Website:

Special Issue Call for Papers:

Special Issue Information

Dear Colleagues,

Despite the recent advances of 5G and beyond systems and multimedia coding techniques, the increasing demand for ubiquitous delivery of high-quality multimedia data ranging from high resolution video to immersive applications including AR/VR/MR continues to pose significant challenges for existing multimedia coding techniques and communication platforms that struggle to deal with the stringent requirements for low latency, high bandwidth, and ultra reliability. Machine learning has recently attracted significant attention from the multimedia community as the key enabler towards designing and building more reliable, efficient, and scalable multimedia communication systems. This Special Issue will publish the latest research and findings in machine learning enabled multimedia coding and communication systems for improved resilience, efficient coding, and reduced latency.

Topics of interest include but are not limited to the following:

Machine learning for image/video communications
Machine learning for immersive communications
Machine learning for resource allocation in multimedia communications
Rate control for machine learning based video coding
Machine learning for image/video coding
Machine learning for network orchestration in multimedia applications
Machine learning-based multimedia quality assessment
Machine learning for multimedia enabled IoT
Machine learning assisted cloud/edge/fog management for multimedia applications

Special Issue Editors

Dr. Nikolaos Thomos
Guest Editor
University of Essex, Colchester, UK
Interests: machine learning for communications; multimedia communications; network coding; information-centric networking; joint source and channel coding; signal processing and sensor networks
Special Issues and Collections in MDPI journals

Dr. Eirina Bourtsoulatze
Guest Editor
University of Essex, Colchester, UK
Interests: deep neural networks for joint source-channel coding; machine learning; network coding; wireless edge caching; multimedia communications

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI\’s English editing service prior to publication or during author revisions.

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