Human–machine partnerships at the exascale: exploring simulation ensembles through image databases
Author:
Funder
Los Alamos National Laboratory
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s12650-024-00999-7.pdf
Reference48 articles.
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2. Bauer AC, Abbasi H, Ahrens J, et al (2016) In situ methods, infrastructures, and applications on high performance computing platforms. In: Computer Graphics Forum, Wiley Online Library, pp 577–597. https://doi.org/10.1111/cgf.12930
3. Bensema K, Gosink L, Obermaier H et al (2015) Modality-driven classification and visualization of ensemble variance. IEEE Trans Visual Comput Graphics 22(10):2289–2299. https://doi.org/10.1109/TVCG.2015.2507569
4. Chen X, Li J, Zhang Y et al (2020) Automatic feature extraction in x-ray image based on deep learning approach for determination of bone age. Futur Gener Comput Syst 110:795–801. https://doi.org/10.1016/j.future.2019.10.032
5. Dahshan M, Polys N, Jayne R, et al (2020) Making sense of scientific simulation ensembles with semantic interaction. In: Computer Graphics Forum, Wiley Online Library, pp 325–343. https://doi.org/10.1111/cgf.14029
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