Following the success of the first Reproducible Research on Pattern Recognition workshop that was held at the previous ICPR event in 2016, we propose the second edition in the same spirit as the previous event with a special focus on Digital Geometry and Mathematical Morphology. As for the previous edition, it is intended as both a short participative course on the RR aspects, leading to open discussions with the participants, or also as a practical workshop on how to actually perform RR.

Important dates

Submission deadline: May 28, 2018 

Author notification: July 6, 2018

Camera-ready: July 16, 2018

Call For Paper (pdf)

This Call for Papers expects two kinds of contributions.

The first (Track 1 on RR Framework) is dedicated to the general topics of Reproducible Research in Computer Science with a potential link 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:

  • 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

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