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- W2896736136 abstract "Exploring large medical image sets by means of traditional similarity query criteria (e.g., neighborhood) can be fruitless if retrieved images are too similar among themselves. This demonstration introduces Kundaha, an exploration tool that assists experts in retrieving and navigating on results from a diversified similarity perspective of user-posed queries. Its implementation includes a wide set of metrics, descriptors, and indexes for enhancing query execution. Users can combine such features with diversified similarity criteria for the organized exploration of result sets and also employ relevance feedback cycles for finding new query-based viewpoints." @default.
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- W2896736136 date "2018-10-17" @default.
- W2896736136 modified "2023-10-02" @default.
- W2896736136 title "Exploring Diversified Similarity with Kundaha" @default.
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- W2896736136 doi "https://doi.org/10.1145/3269206.3269220" @default.
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