Fight the Pandemic: Highlights from the 2020 IEEE 5-Minute Video Clip Contest [SP Competitions]

Tirza Routtenberg; Alberto Carini; Emilie Chouzenoux; Piya Pal; Jose C.M. Bermudez; Lucio Marcenaro

doi:https://doi.org/10.1109/MSP.2020.3046230

Fight the Pandemic: Highlights from the 2020 IEEE 5-Minute Video Clip Contest [SP Competitions]

Tirza Routtenberg, Alberto Carini, Emilie Chouzenoux, Piya Pal, Jose C.M. Bermudez, Lucio Marcenaro

Department of Electrical & Computer Engineering

Ben-Gurion University of the Negev

Research output: Contribution to journal › Article › peer-review

Abstract

The annual IEEE 5-Minute Video Clip Contest (5-MICC) was launched by the IEEE Signal Processing Society (SPS), and the selected topic for the competition at IEEE ICIP 2020 was Fight the Pandemic. The organizing committee selected three finalist videos and placed them online for public voting. The first one is about a visual analytic system for pandemic management, the second concerns machine learning screening of coronavirus disease (COVID-19) patients based on X-ray images, and the third deals with a COVID-19 test strip reader. Taking the public voting results from more than 800 participants into consideration, the panel of judges decided the final rankings of the three videos. In this article, we present an overview of the 5-MICC at ICIP 2020, describing the competition setup, the teams, and their approaches. We also share our experience and the feedback we received from the finalists.

Original language	American English
Article number	9363512
Pages (from-to)	138-143
Number of pages	6
Journal	IEEE Signal Processing Magazine
Volume	38
Issue number	2
DOIs	https://doi.org/10.1109/MSP.2020.3046230
State	Published - 1 Mar 2021

All Science Journal Classification (ASJC) codes

Signal Processing
Applied Mathematics
Electrical and Electronic Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

https://doi.org/10.1109/MSP.2020.3046230

Cite this

@article{7f211b0f9fcc4a638bee7008de81b1e2,

title = "Fight the Pandemic: Highlights from the 2020 IEEE 5-Minute Video Clip Contest [SP Competitions]",

abstract = "The annual IEEE 5-Minute Video Clip Contest (5-MICC) was launched by the IEEE Signal Processing Society (SPS), and the selected topic for the competition at IEEE ICIP 2020 was Fight the Pandemic. The organizing committee selected three finalist videos and placed them online for public voting. The first one is about a visual analytic system for pandemic management, the second concerns machine learning screening of coronavirus disease (COVID-19) patients based on X-ray images, and the third deals with a COVID-19 test strip reader. Taking the public voting results from more than 800 participants into consideration, the panel of judges decided the final rankings of the three videos. In this article, we present an overview of the 5-MICC at ICIP 2020, describing the competition setup, the teams, and their approaches. We also share our experience and the feedback we received from the finalists.",

author = "Tirza Routtenberg and Alberto Carini and Emilie Chouzenoux and Piya Pal and Bermudez, {Jose C.M.} and Lucio Marcenaro",

note = "Publisher Copyright: {\textcopyright} 1991-2012 IEEE.",

year = "2021",

month = mar,

day = "1",

doi = "https://doi.org/10.1109/MSP.2020.3046230",

language = "American English",

volume = "38",

pages = "138--143",

journal = "IEEE Signal Processing Magazine",

issn = "1053-5888",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "2",

}

TY - JOUR

T1 - Fight the Pandemic

T2 - Highlights from the 2020 IEEE 5-Minute Video Clip Contest [SP Competitions]

AU - Routtenberg, Tirza

AU - Carini, Alberto

AU - Chouzenoux, Emilie

AU - Pal, Piya

AU - Bermudez, Jose C.M.

AU - Marcenaro, Lucio

PY - 2021/3/1

Y1 - 2021/3/1

N2 - The annual IEEE 5-Minute Video Clip Contest (5-MICC) was launched by the IEEE Signal Processing Society (SPS), and the selected topic for the competition at IEEE ICIP 2020 was Fight the Pandemic. The organizing committee selected three finalist videos and placed them online for public voting. The first one is about a visual analytic system for pandemic management, the second concerns machine learning screening of coronavirus disease (COVID-19) patients based on X-ray images, and the third deals with a COVID-19 test strip reader. Taking the public voting results from more than 800 participants into consideration, the panel of judges decided the final rankings of the three videos. In this article, we present an overview of the 5-MICC at ICIP 2020, describing the competition setup, the teams, and their approaches. We also share our experience and the feedback we received from the finalists.

AB - The annual IEEE 5-Minute Video Clip Contest (5-MICC) was launched by the IEEE Signal Processing Society (SPS), and the selected topic for the competition at IEEE ICIP 2020 was Fight the Pandemic. The organizing committee selected three finalist videos and placed them online for public voting. The first one is about a visual analytic system for pandemic management, the second concerns machine learning screening of coronavirus disease (COVID-19) patients based on X-ray images, and the third deals with a COVID-19 test strip reader. Taking the public voting results from more than 800 participants into consideration, the panel of judges decided the final rankings of the three videos. In this article, we present an overview of the 5-MICC at ICIP 2020, describing the competition setup, the teams, and their approaches. We also share our experience and the feedback we received from the finalists.

UR - http://www.scopus.com/inward/record.url?scp=85102052077&partnerID=8YFLogxK

U2 - https://doi.org/10.1109/MSP.2020.3046230

DO - https://doi.org/10.1109/MSP.2020.3046230

M3 - Article

SN - 1053-5888

VL - 38

SP - 138

EP - 143

JO - IEEE Signal Processing Magazine

JF - IEEE Signal Processing Magazine

IS - 2

M1 - 9363512

ER -

Fight the Pandemic: Highlights from the 2020 IEEE 5-Minute Video Clip Contest [SP Competitions]

Abstract

All Science Journal Classification (ASJC) codes

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this