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Peax: Interactive Visual Pattern Search in Sequential Data Using Unsupervised Deep Representation Learning

We present Peax, a novel feature-based technique for interactive visual pattern search in sequential data, like time series or data mapped to a genome sequence. Visually searching for patterns by similarity is often challenging because of the large search space, the visual complexity of patterns, an...

詳細記述

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書誌詳細
出版年:Comput Graph Forum
主要な著者: Lekschas, Fritz, Peterson, Brant, Haehn, Daniel, Ma, Eric, Gehlenborg, Nils, Pfister, Hanspeter
フォーマット: Artigo
言語:Inglês
出版事項: 2020
主題:
オンライン・アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC8323802/
https://ncbi.nlm.nih.gov/pubmed/34334852
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/cgf.13971
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