Group headed by Andreas Bulling of the Human-Computer Interaction and Cognitive Systems department of the University of Stuttgart.
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tab.min.css
Sep 13, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
Cascading Style Sheet - 1.0 KB - MD5: d9abd68a8dbda62de854899073ace28d
tab.min.js
Sep 13, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
Javascript Code - 11.4 KB - MD5: 39e360b1f426670449b2107002d444a0
tests.py
Sep 13, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
Python Source Code - 63 B - MD5: e08f0582500f6562bf0a931ef9503b39
tests.py
Sep 13, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
Python Source Code - 60 B - MD5: 465b7e9f69bfd158c850cdfbc7306818
th.js
Sep 13, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
Javascript Code - 1.0 KB - MD5: f38c20b0221b68924d6c8f0773cb252d
tk.js
Sep 13, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
Javascript Code - 771 B - MD5: 7c572a68c78fb798f11f7d8c78ebb9d6
tooltag-add.svg
Sep 13, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
SVG Image - 331 B - MD5: e59d620a97425b0b1d5c01e0e1711295
tooltag-arrowright.svg
Sep 13, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
SVG Image - 280 B - MD5: bbfb788a849ee115c109b1224a67832b
train_RecallNet.ipynb
Sep 13, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
Jupyter Notebook - 112.9 KB - MD5: 6651f97c9a7a75ed27a0a33f7932747f
transition.css
Sep 13, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
Cascading Style Sheet - 46.2 KB - MD5: ced52703f140c298c600249cebc86be3
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