Zobrazeno 1 - 10
of 266
pro vyhledávání: '"Laramee, Robert S."'
Autor:
Chen, Jian, Isenberg, Petra, Laramee, Robert S., Isenberg, Tobias, Sedlmair, Michael, Moeller, Torsten, Li, Rui
We present and discuss the results of a qualitative analysis of visual representations from images. We labeled each image's essential stimuli, the removal of which would render a visualization uninterpretable. As a result, we derive a typology of 10
Externí odkaz:
http://arxiv.org/abs/2403.05594
Autor:
Bach, Benjamin, Keck, Mandy, Rajabiyazdi, Fateme, Losev, Tatiana, Meirelles, Isabel, Dykes, Jason, Laramee, Robert S., AlKadi, Mashael, Stoiber, Christina, Huron, Samuel, Perin, Charles, Morais, Luiz, Aigner, Wolfgang, Kosminsky, Doris, Boucher, Magdalena, Knudsen, Søren, Manataki, Areti, Aerts, Jan, Hinrichs, Uta, Roberts, Jonathan C., Carpendale, Sheelagh
This paper is a call to action for research and discussion on data visualization education. As visualization evolves and spreads through our professional and personal lives, we need to understand how to support and empower a broad and diverse communi
Externí odkaz:
http://arxiv.org/abs/2308.07703
Autor:
Chen, Jian, Isenberg, Petra, Laramee, Robert S., Isenberg, Tobias, Sedlmair, Michael, Moeller, Torsten, Shen, Han-Wei
We present and discuss the results of a two-year qualitative analysis of images published in IEEE Visualization (VIS) papers. Specifically, we derive a typology of 13 visualization image types, coded to distinguish visualizations and several image ch
Externí odkaz:
http://arxiv.org/abs/2209.07533
Autor:
Dykes, Jason, Abdul-Rahman, Alfie, Archambault, Daniel, Bach, Benjamin, Borgo, Rita, Chen, Min, Enright, Jessica, Fang, Hui, Firat, Elif E., Freeman, Euan, Gonen, Tuna, Harris, Claire, Jianu, Radu, John, Nigel W., Khan, Saiful, Lahiff, Andrew, Laramee, Robert S., Matthews, Louise, Mohr, Sibylle, Nguyen, Phong H., Rahat, Alma A. M., Reeve, Richard, Ritsos, Panagiotis D., Roberts, Jonathan C., Slingsby, Aidan, Swallow, Ben, Torsney-Weir, Thomas, Turkay, Cagatay, Turner, Robert, Vidal, Franck P., Wang, Qiru, Wood, Jo, Xu, Kai
Publikováno v:
RSTA: Special Issue - Technical challenges of modelling real-life epidemics and examples of overcoming these, 380(2233) 2022
We report on an ongoing collaboration between epidemiological modellers and visualization researchers by documenting and reflecting upon knowledge constructs -- a series of ideas, approaches and methods taken from existing visualization research and
Externí odkaz:
http://arxiv.org/abs/2204.06946
Autor:
Diehl, Alexandra, Abdul-Rahman, Alfie, Bach, Benjamin, El-Assady, Mennatallah, Kraus, Matthias, Laramee, Robert S., Keim, Daniel A., Chen, Min
Grounded theory (GT) is a research methodology that entails a systematic workflow for theory generation grounded on emergent data. In this paper, we juxtapose GT workflows with typical workflows in visualization and visual analytics, shortly VIS, and
Externí odkaz:
http://arxiv.org/abs/2203.01777
Publikováno v:
In Visual Informatics September 2024 8(3):57-70
Autor:
Liu, Xiaoxiao, Alharbi, Mohammad, Best, Joe, Chen, Jian, Diehl, Alexandra, Firat, Elif, Rees, Dylan, Wang, Qiru, Laramee, Robert S
Visualization, as a vibrant field for researchers, practitioners, and higher educational institutions, is growing and evolving very rapidly. Tremendous progress has been made since 1987, the year often cited as the beginning of data visualization as
Externí odkaz:
http://arxiv.org/abs/2108.08907
Autor:
Ling, Meng, Chen, Jian, Möller, Torsten, Isenberg, Petra, Isenberg, Tobias, Sedlmair, Michael, Laramee, Robert S., Shen, Han-Wei, Wu, Jian, Giles, C. Lee
Publikováno v:
International Conference on Document Analysis and Recognition (ICDAR), 2021
We present document domain randomization (DDR), the first successful transfer of convolutional neural networks (CNNs) trained only on graphically rendered pseudo-paper pages to real-world document segmentation. DDR renders pseudo-document pages by mo
Externí odkaz:
http://arxiv.org/abs/2105.14931
Autor:
Chen, Jian, Ling, Meng, Li, Rui, Isenberg, Petra, Isenberg, Tobias, Sedlmair, Michael, Möller, Torsten, Laramee, Robert S., Shen, Han-Wei, Wünsche, Katharina, Wang, Qiru
Publikováno v:
IEEE Transactions on Visualization and Computer Graphics 27(9), 2021
We present the VIS30K dataset, a collection of 29,689 images that represents 30 years of figures and tables from each track of the IEEE Visualization conference series (Vis, SciVis, InfoVis, VAST). VIS30K's comprehensive coverage of the scientific li
Externí odkaz:
http://arxiv.org/abs/2101.01036
Publikováno v:
Big Data Research, 15, 29-42 (2019)
In this paper we demonstrate the use of multivariate topological algorithms to analyse and interpret Lattice Quantum Chromodynamics (QCD) data. Lattice QCD is a long established field of theoretical physics research in the pursuit of understanding th
Externí odkaz:
http://arxiv.org/abs/1904.00504