Demo: Deep Joint Source-Channel Coding for Underwater Image Transmission

Khizar Anjum; Zhuoran Qi; Dario Pompili

doi:10.1145/3567600.3569542

Demo: Deep Joint Source-Channel Coding for Underwater Image Transmission

Khizar Anjum, Zhuoran Qi, Dario Pompili

School of Engineering, Electrical & Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Traditional methods for coding underwater acoustic communications are bound to be surpassed by methods optimizing for source-channel coding jointly. However, the complexity of joint-optimization has thwarted successful breakthroughs in this area. We, therefore, present a novel approach, where we model the coding problem as the translation problem of the input sequence to another glanguage', depending on the estimated channel conditions.

Original language	English (US)
Title of host publication	WUWNet 2022 - 16th International Conference on Underwater Networks and Systems
Publisher	Association for Computing Machinery
ISBN (Electronic)	9781450399524
DOIs	https://doi.org/10.1145/3567600.3569542
State	Published - Nov 14 2022
Event	16th International Conference on Underwater Networks and Systems, WUWNet 2022 - Boston, United States Duration: Nov 14 2022 → Nov 16 2022

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	16th International Conference on Underwater Networks and Systems, WUWNet 2022
Country/Territory	United States
City	Boston
Period	11/14/22 → 11/16/22

All Science Journal Classification (ASJC) codes

Human-Computer Interaction
Computer Networks and Communications
Computer Vision and Pattern Recognition
Software

Access to Document

10.1145/3567600.3569542

Cite this

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title = "Demo: Deep Joint Source-Channel Coding for Underwater Image Transmission",

abstract = "Traditional methods for coding underwater acoustic communications are bound to be surpassed by methods optimizing for source-channel coding jointly. However, the complexity of joint-optimization has thwarted successful breakthroughs in this area. We, therefore, present a novel approach, where we model the coding problem as the translation problem of the input sequence to another glanguage', depending on the estimated channel conditions.",

author = "Khizar Anjum and Zhuoran Qi and Dario Pompili",

note = "Publisher Copyright: {\textcopyright} 2022 Owner/Author.; 16th International Conference on Underwater Networks and Systems, WUWNet 2022 ; Conference date: 14-11-2022 Through 16-11-2022",

year = "2022",

month = nov,

day = "14",

doi = "10.1145/3567600.3569542",

language = "English (US)",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

booktitle = "WUWNet 2022 - 16th International Conference on Underwater Networks and Systems",

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Anjum, K, Qi, Z & Pompili, D 2022, Demo: Deep Joint Source-Channel Coding for Underwater Image Transmission. in WUWNet 2022 - 16th International Conference on Underwater Networks and Systems., 29, ACM International Conference Proceeding Series, Association for Computing Machinery, 16th International Conference on Underwater Networks and Systems, WUWNet 2022, Boston, United States, 11/14/22. https://doi.org/10.1145/3567600.3569542

Demo : Deep Joint Source-Channel Coding for Underwater Image Transmission. / Anjum, Khizar; Qi, Zhuoran; Pompili, Dario.

WUWNet 2022 - 16th International Conference on Underwater Networks and Systems. Association for Computing Machinery, 2022. 29 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Anjum, Khizar

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AU - Pompili, Dario

PY - 2022/11/14

Y1 - 2022/11/14

N2 - Traditional methods for coding underwater acoustic communications are bound to be surpassed by methods optimizing for source-channel coding jointly. However, the complexity of joint-optimization has thwarted successful breakthroughs in this area. We, therefore, present a novel approach, where we model the coding problem as the translation problem of the input sequence to another glanguage', depending on the estimated channel conditions.

AB - Traditional methods for coding underwater acoustic communications are bound to be surpassed by methods optimizing for source-channel coding jointly. However, the complexity of joint-optimization has thwarted successful breakthroughs in this area. We, therefore, present a novel approach, where we model the coding problem as the translation problem of the input sequence to another glanguage', depending on the estimated channel conditions.

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M3 - Conference contribution

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PB - Association for Computing Machinery

Y2 - 14 November 2022 through 16 November 2022

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Demo: Deep Joint Source-Channel Coding for Underwater Image Transmission

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