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MDRE 2019 : First MMM Special Session on Multimedia Datasets for Repeatable Experimentation

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Link: http://mmm2019.iti.gr/multimedia-datasets-for-repeatable-experimentation-ss3mdre/
 
When Jan 8, 2019 - Jan 11, 2019
Where Thessaloniki, Greece
Submission Deadline Jul 30, 2018
Notification Due Sep 17, 2018
Final Version Due Oct 12, 2018
Categories    multimedia   dataset   evaluation   video
 

Call For Papers

Information retrieval and multimedia content access has a long history of comparative evaluation and many of the advances in the area over the past decade can be attributed to the availability of open datasets that support comparative and repeatable experimentation. Sharing data and code to allow other researchers to replicate research results is needed in the multimedia modeling field and helps to improve the performance of systems and the reproducibility of published papers. The main focus in on datasets, and researchers within the multimedia community are encouraged to submit their datasets to the MDRE special session. Authors of relevant open-source experimental frameworks are also encourage to submit their work. Authors are asked to provide a paper describing the motivation, design, and usage of the dataset or framework, as well as a brief summary of the experiments performed to date, and are requested to highlight how this work useful to the community.

The benefits for authors who successfully submit are:
Accepted contributions will be included in the MMM conference proceedings, as part of the Lecture Notes in Computer Science (LNCS) series by Springer. Authors of selected MMM papers will be invited to publish extended versions in a journal special issue. Accepted contributions will be listed in a recognized index of multimedia datasets and frameworks, thereby increasing their visibility. Authors of accepted contributions will be invited to present their dataset (or framework) as part of the special session at MMM 2019.

Regarding the submission of a dataset, the authors should make it available by providing a public URL for download, as mentioned above, and agree to the link being maintained on an MMM datasets dedicated site. All datasets must be licensed in such a manner that it can be legally and freely used with all appropriate ethical approvals completed. Authors are encouraged to prepare appropriate and helpful documentation to accompany the dataset, including examples of how it can be used by the community, examples of successful usage and restrictions on usage. There are similar expectations for the open-source frameworks.

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