Call for IEEE SPAWC Data Competition Paper Submissions & Competitors!

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IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC) 
2021
September 27 – 30, 2021  --   Lucca, Italy (And Online Hybrid Event)

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SPAWC is hosting two exciting data competition this year at the intersection of 
wireless communications and machine learning and soliciting competitors both 
through paper submissions on approaches to these problems and through direct 
participation in the competitions through submission of scored results.

We will accept the submission of full papers with proposed approaches and 
solutions to the data competition problem statements and datasets through July 
5th and will accept competition solution entries through the beginning of the 
conference on September 27th through the data competition sites hosted on 
Kaggle and eval.ai.

Full details for the data competition event may be found at the official 
conference website at https://www.spawc2021.com/data-competition/
Challenge #1 (Industrial Multi-Domain Localization) focuses on Industry 4.0 
centric robust and versatile positioning of robotic devices using a combination 
of Camera-based, IMU-Based and ultra-wideband (UWB) based data observations 
requiring the fusion of multiple domains of observation to maximize precision.  
As robust and precise radio emitter localization is a key component in future 
industry and factory applications, we are excited to launch this data-driven 
challenge as part of SPAWC 21.
https://www.kaggle.com/c/ieeespawc21localization/data

Challenge #2 (Wideband Signal Recognition) focuses on rapid spectrum awareness 
and signal recognition to enable radio spectrum access coordination, anomaly 
detection, spectrum sharing, spectrum analytics and spectrum monitoring 
applications.  As real-time spectrum awareness and spectrum aware decision 
making may be key components to beyond-5G and 6G communications systems, we are 
excited to launch this data-driven signal recognition competition as part of 
SPAWC this year to compare and contrast new promising approaches to the problem.
https://eval.ai/web/challenges/challenge-page/1057/overview

Both address key challenge areas where machine learning has demonstrated 
extremely promising initial results in related areas, but where we believe 
these datasets provide an exciting new step in expanding these results to 
multi-domain and to broad recognition challenges beyond what has been the 
principal focus in research publications thus far.   Thus, we hope by posing 
these two challenges we can excite new researchers to propose, compare and 
publish new approaches to these problems which can help accelerate and mature 
these domains at the intersection of communications systems and machine 
learning.

We’re soliciting full workshop papers via EDAS 
(https://edas.info/newPaper.php?c=28267) from competitors wishing to publish 
their approaches and ideas as well as competition submissions via Kaggle and 
eval.ai which may be submitted directly via the competition websites above 
until the beginning of the Conference event.

Best Regards,
Tim O’Shea
Data Competition Chair, SPAWC21

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