Flow Field Reduction Via Reconstructing Vector Data From 3-D Streamlines Using Deep Learning
We present a new approach for streamline-based flow field representation and reduction. Our method can work in the in situ visualization setting by tracing streamlines from each time step of the simulation and storing compressed streamlines for post hoc analysis where users can afford longer reconst...
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Détails bibliographiques
| Publié dans: | IEEE computer graphics and applications. - 1997. - 39(2019), 4 vom: 25. Juli, Seite 54-67
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| Auteur principal: |
Han, Jun
(Auteur) |
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| Autres auteurs: |
Tao, Jun,
Zheng, Hao,
Guo, Hanqi,
Chen, Danny Z,
Wang, Chaoli |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2019
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| Accès à la collection: | IEEE computer graphics and applications
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| Sujets: | Journal Article |
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