Aim

Following the success of the first and second workshop on Reproducible Research on Pattern Recognition that were held at the previous ICPR conferences in 2016 and 2018, we propose the third edition in the same spirit as the previous event. As was the case for the previous two editions, RRPR 2020 is intended as both a short participative course on the RR aspects, leading to open discussions with the participants,  and also as a practical workshop on how to actually perform RR. In addition, another key goal for gathering the research community is to further advance the scientific aspects of reproducibility in pattern recognition research. 

This workshop is of interest for all ICPR participants attendees since it allows to handle various topics not restricted to one specific fields. The reproducibility is an important topics in general and particularly good for PhD students and young researchers to learn "good habits". A special track on Geometry and Deep Learning is proposed for this new edition (not exclusive).

Important dates (tentative) & communication

  • Start communication on Workshop proposal: 24 January
  • Early submission deadline: July 15th. (updated)
  • Author notification: August 15th. (updated)
  • Second round submission deadline: October 10th.
  • Author notification November 10th
Updated: Authors of already acceped papers to ICPR 2020 are invited to submit short papers extension describing the reproducibility of their work.

Call For Paper (tentative)

This Call for Papers expects two kinds of contributions.

The first (Track 1 on RR Frameworks) is dedicated to the general topics of Reproducible Research in experimental Computer Science with clear links to Image Processing and Pattern Recognition. Papers describing experiences, frameworks or platforms are welcome. The contributions might also include discussions on software libraries, experiences highlighting how the works benefit from Reproducible Research.

In the second kind of contributions (Track 2 on RR Results), authors will be invited to describe their works in terms of Reproducible Research. For example, authors of papers already accepted to ICPR might propose a companion paper describing the quality of the reproducible aspects. In particular the papers of this track can focus mainly (but not limited) for instance on:

  • Algorithmic implementation details
  • Link to implementation with source code given by the authors (for example, a link to GitHub or to the website of the author).
  • Influence of parameter(s) for the result quality (criteria to optimize them).
  • Integration of source code in an other framework.
  • Known limitations (or difficult cases).
  • Future improvements.
  • Installation procedure.

For this track, the topics could overlap with the main topics of the ICPR tracks:

  • Geometry and Deep Learning (special track)
  • Discrete Geometry and Mathematical Morphology
  • Pattern Recognition and Machine Learning
  • Computer Vision and Robot Vision
  • Image, Speech, Signal, and Video Processing
  • Document Analysis, Biometrics, and Pattern Recognition Applications.
  • Biomedical Image Analysis and Applications

Sponsors and endorsements

Follow us on twitter

(other sponsors will appears here after official start)

logoICPR
lirisLogo
lirisLogotc18Sponsor
e
Online user: 1 RSS Feed