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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...
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| 出版年: | Comput Graph Forum |
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| 主要な著者: | , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2020
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| 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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