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@@ -10,10 +10,10 @@ Participants address these challenges by creating algorithms for analyzing, expl
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making it possible to establish the state of the art and track progress. Our larger aim is to promote reproducible research that makes multimedia a positive force for society.
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MediaEval goes beyond other benchmarks and data science challenges in that it also pursues a “Quest for Insight” (Q4I). With Q4I we push beyond only striving to improve evaluation
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scores to also working to achieve deeper understanding about the challenges. For example, properties of the data, strengths and weaknesses of particular types of approaches, and observations
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scores to also working to achieve deeper understanding about the challenges. For example, characteristics of the data, strengths and weaknesses of particular types of approaches, and observations
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about the evaluation procedure.
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Currently, MediaEval is calling for task proposals, see the call for proposals [link](https://multimediaeval.github.io/2024/09/24/call.html).
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Currently, MediaEval is calling for task proposals, see the [call for proposals](https://multimediaeval.github.io/2024/09/24/call.html).
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Watch here for announcements of the tasks that will be offered in MediaEval 2025.
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