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<!DOCTYPE html>
<html lang="en" dir="ltr">
<head>
<meta
name="description"
content="EYRA is a platform for benchmarking the performance of scientific algorithms"
/>
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<title>EYRA Benchmark Platform</title>
<meta
name="viewport"
content="width=device-width,minimum-scale=1,initial-scale=1"
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<title>About | EYRA Benchmark Platform</title>
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<h5>
Enhance-Your-Research Alliance (EYRA) benchmark platform
</h5>
</div>
<p>
The
<strong
><a href="https://esciencecenter.nl/"
>Netherlands eScience Center</a
></strong
>
and
<strong><a href="https://www.surf.nl/en">SURF</a></strong>
formed an alliance with the mission to enhance research by
providing an online platform to benchmark the performance of
research software. The platform is available for researchers
from all scientific disciplines, from physics and astronomy to
humanities, social sciences and life sciences.
</p>
<p>
This project is led by Adriënne Mendrik (Netherlands eScience
Center) and Annette Langedijk (SURF). Contact us if you would
like to collaborate or set-up a benchmark:
<a href="mailto: [email protected]"
>.
</p>
<pre></pre>
<h3>Why Benchmarking?</h3>
<p>
One of the currently most well-known benchmarks for algorithm
performance is<strong> </strong
><a href="http://www.image-net.org/"
><strong></strong>ImageNet</a
>. In 2012, the ImageNet challenge [1,2] boosted the field of
Artificial Intelligence by showing a drastic improvement in
performance after the submission of a deep convolutional neural
network (CNN) called AlexNet [3]. In various scientific
disciplines there is a growing interest to benchmark algorithm
performance on research data using the same data, metrics and
ground truth to compare their performance for a specific task.
Translating research questions into a benchmark design has the
potential to lead to scientific breakthroughs. The point of
benchmarking is to test the current status of algorithms,
identify opportunities for improvement, and learn from eachother
in order to enhance research.
</p>
<p>
[1]
<a href="https://en.wikipedia.org/wiki/ImageNet"
>https://en.wikipedia.org/wiki/ImageNet</a
><br />[2]
<a
href="https://www.economist.com/news/special-report/21700756-artificial-intelligence-boom-based-old-idea-modern-twist-not"
>"From not working to neural networking"</a
>. <em>The Economist</em>. 25 June 2016. Retrieved 19 April
2019. <br />[3] Krizhevsky, Alex, Ilya Sutskever, and Geoffrey
E. Hinton. "Imagenet classification with deep convolutional
neural networks."
<em>Advances in neural information processing systems</em>,
2012.
</p>
<pre></pre>
<h3>Why EYRA?</h3>
<p>
We aim to offer a platform to easily set-up and participate in
benchmarks for research. We aim to provide:
</p>
<ul>
<li>Instructions on how to set-up a benchmark</li>
<li>
Algorithm submission in docker containers, such that
algorithms can be run in the cloud on the testing data.
</li>
<li>
Automatically generated leaderboard and analysis beyond the
leaderboard to identify strengths and weaknesses.
</li>
<li>
FAIR (Findable, Accessible, Interoperable, and Reusable)
benchmarks, data, algorithms, and evaluation metrics.
</li>
<li>SURF infrastructure.</li>
<li>
Connect people from different scientific disciplines and
promote cross-fertilization.
</li>
</ul>
<p>
<em
>We are not there yet.
<strong
>The platform is still actively under development. </strong
>Click the
<strong><a href="#subscribe">Subscribe</a> </strong>button at
the bottom of the page to stay up to date.</em
>
</p>
<h2><br />Source code</h2>
<p>
EYRA repository:
<a href="https://github.com/EYRA-Benchmark"
>https://github.com/EYRA-Benchmark</a
>
</p>
<p>
The EYRA benchmark platform is an open source platform based on
the open source
<a href="https://grand-challenge.org/Create_your_own_challenge/"
>COMIC platform</a
>, which is associated to
<a href="https://grand-challenge.org/">grand-challenge.org</a>.
</p>
<pre></pre>
<h2>Acknowledgements</h2>
<p>
We would like to acknowledge the people below for their
contribution to the EYRA benchmark platform.
</p>
<h4>Netherlands eScience Center</h4>
<p>
Tom Klaver, Pushpanjali Pawar, Maarten van Meersbergen, Roel
Zinkstok, Carlos Martinez-Ortiz, Alessio Sclocco, Rena Bakhshi,
Romulo Goncalves, Evelien Schat.
</p>
<h4>SURF</h4>
<p>
Maurice Bouwhuis, Mary Hester, Jan Bot, Haukur Pall Jonsson,
Giuseppe Gianquitto, Ymke van den Berg, Martin Brandt.
</p>
<h4>COMIC Platform</h4>
<p>
James Meakin (Radboud UMC), Bram van Ginneken (Radboud UMC).
</p>
<h4>Platform Requirements</h4>
<p>
Maria Eskevich (CLARIN ERIC), Melvin Wevers (Digital Humanities
Lab, KNAW Humanities Cluster), Mike Lees (UvA), Marius Staring