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Editorial: Intelligent Signal Analysis for Contagious Virus Diseases

Schuller, Bjorn W.; Eldar, Yonina; Pantic, Maja; Narayanan, Shrikanth; Virtanen, Tuomas; Tao, Jianhua (2022-02)

 
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IEEE_JSTSP_SI_COVID_Editorial_2.pdf (2.390Mt)
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Schuller, Bjorn W.
Eldar, Yonina
Pantic, Maja
Narayanan, Shrikanth
Virtanen, Tuomas
Tao, Jianhua
02 / 2022

IEEE Journal on Selected Topics in Signal Processing
This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
doi:10.1109/JSTSP.2022.3160023
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202210287987

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Non peer reviewed
Tiivistelmä
<p>COVID-19 infection-s recent outbreak triggered by the SARS-CoV-2 Corona virus had already led to more than two million reported infected individuals when we first addressed the community by our call - by now, the number sadly rose to roughly half a billion cases worldwide. The outbreak of COIVD-19 has also re-shaped and accelerated the scientific publication landscape in no time. One can observe a massive uprise in interest in work related to the topic of highly contagious virus diseases and potential contributions of digital health including intelligent signal processing. In addition, most publishers have reacted in one or the other way to the crises such as by opening up to pre-prints, waiving publication fees for COVID-19-related research, providing search functions and tools for COVID-19 research, and many more. Here, we gathered 13 carefully selected novel contributions across signal types such as audio, speech, image, video, or symbolic information, as well as their multimodal combination for application in the risk assessment, diagnosis, and monitoring of contagious virus diseases. </p>
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