IDLat : An Importance-Driven Latent Generation Method for Scientific Data
Deep learning based latent representations have been widely used for numerous scientific visualization applications such as isosurface similarity analysis, volume rendering, flow field synthesis, and data reduction, just to name a few. However, existing latent representations are mostly generated fr...
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Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on visualization and computer graphics. - 1996. - 29(2023), 1 vom: 27. Jan., Seite 679-689
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| 1. Verfasser: |
Shen, Jingyi
(VerfasserIn) |
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| Weitere Verfasser: |
Li, Haoyu,
Xu, Jiayi,
Biswas, Ayan,
Shen, Han-Wei |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2023
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on visualization and computer graphics
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| Schlagworte: | Journal Article |
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