Group headed by Andreas Bulling of the Human-Computer Interaction and Cognitive Systems department of the University of Stuttgart.
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1,081 to 1,090 of 1,117 Results
xception_custom.py
Sep 13, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
Python Source Code - 14.0 KB - MD5: c94dea75ef2c5e2eda6a1ac97bfe3ea4
xregexp.js
Sep 13, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
Javascript Code - 226.9 KB - MD5: efda034b953739111c7e06101843860a
xregexp.min.js
Sep 13, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
Javascript Code - 122.3 KB - MD5: b0439563a5d3ea2d52435768fd01238e
zh-CN.js
Sep 13, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
Javascript Code - 768 B - MD5: 2cff662ec5f972b4613566cf5988cda2
zh-TW.js
Sep 13, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
Javascript Code - 707 B - MD5: 04554a227c2ba0f3bb6ca3d2e01e5440
Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
Jun 21, 2022 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"
Wang, Yao; Bulling, Andreas, 2022, "Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"", https://doi.org/10.18419/DARUS-2826, DaRUS, V1, UNF:6:AuvgRc09o1rESd63AqlW9Q== [fileUNF]
Despite its importance for assessing the effectiveness of communicating information visually, fine-grained recallability of information visualisations has not been studied quantitatively so far. We propose a question-answering paradigm to study visualisation recallability and present VisRecall -- a novel dataset consisting of 200 information visual...
10_blur.zip
Jun 21, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
ZIP Archive - 4.6 MB - MD5: 4f82bd8d7e56649dc799dc0153f35189
10.zip
Jun 21, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
ZIP Archive - 3.7 MB - MD5: 0302e172f0cdb8cef6a84f4ecfb31caf
1_blur.zip
Jun 21, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
ZIP Archive - 2.3 MB - MD5: 01535147f2b09ae9ce65b154af5f2ba4
1.zip
Jun 21, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"
ZIP Archive - 1.5 MB - MD5: 617d99e6308bb96a9ae502bb01c9d0f8
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