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Jian
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Chen

Datasets & Competitions

This dataport will be useful to those interested in visual design for complex physics phenomena. We have included two quantum physics data sample datasets and our empirical study results. 

(1) evaluation results from two experiments (20 participants in each and 40 in total) to empirically validate that separable bivariate pairs of large-magnitude-range vector 

magnitude representations are more efficient than integral pairs. 

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108 Views

This dataset contains three benchmark datasets as part of the scholarly output of an ICDAR 2021 paper: 

Meng Ling, Jian Chen, Torsten Möller, Petra Isenberg, Tobias Isenberg, Michael Sedlmair, Robert S. Laramee, Han-Wei Shen, Jian Wu, and C. Lee Giles, Document Domain Randomization for Deep Learning Document Layout Extraction, 16th International Conference on Document Analysis and Recognition (ICDAR) 2021. September 5-10, Lausanne, Switzerland. 

This dataset contains nine class lables: abstract, algorithm, author, body text, caption, equation, figure, table, and title.

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625 Views

A collection of about 30K images that represents figures and tables from each track of the IEEE Visualization conference series (Vis, SciVis, InfoVis, VAST).

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1630 Views