Cross-device Comparison
Cross-Device Comparison is a methodological framework within cross-device collaborative visualization that enables users to systematically analyze and juxtapose datasets or visual representations across multiple heterogeneous devices, distinguished by its support for synchronous, coordinated interactions and consistent state management despite differing screen sizes, input modalities, and device capabilities.
20
Publications
909
Citations
102
Authors
40
Institutions
Publications per year
2017–2026
12
20
Frederik Brudy, Christian Holz, Roman Rädle et al. · 2019 · 284 citations
Arts, Computer Science, Design +15
Towards Device-Agnostic Mobile Cough Detection with Convolutional Neural Networks
Filipe Barata, Kevin Kipfer, Maurice Weber et al. · 2019 · 70 citations · Full text
1–5 of 20
102
2
h-index
2
h-index
2
h-index
2
h-index
2
h-index
1–5 of 102
40
ETH Zurich
Zurich, Switzerland
3 h-index
11 publications
413 citations
University College London
London, United Kingdom
2 h-index
4 publications
600 citations
Fusion (United States)
Houston, United States
2 h-index
7 publications
77 citations
University of Konstanz
Konstanz, Germany
2 h-index
9 publications
141 citations
Plasma Technology (United States)
Torrance, United States
2 h-index
4 publications
140 citations
Fusion Academy
Grand Rapids, United States
2 h-index
4 publications
140 citations
Salesforce (United States)
San Francisco, United States
1 h-index
4 publications
420 citations

Aarhus University
Aarhus, Denmark
1 h-index
2 publications
568 citations
1–8 of 40
1 publications · 41 citations
1
h-index
1 publications · 17 citations
1
h-index
Repository · 1 publications · 16 citations
1
h-index
Conference · 1 publications · 105 citations
1
h-index
1 publications · 18 citations
1
h-index
1–5