Daniel Sonntag

2.3k citations
135 papers · 989 indexed · h-index 17

Impact in

Papers in

Daniel Sonntag

123 papers receiving 946 citations

Peers

Daniel Sonntag
Comparison fields: 5 of 109
  • Human-Computer Interaction 357
  • Health Informatics 57
  • Computer Vision and Pattern Recognition 344
  • Artificial Intelligence 325
  • Cognitive Neuroscience 124
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Mike Wu United States
Rubén Tolosana Spain
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Iain McCowan Switzerland
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Sonntag

Since Specialization
Citations

This map shows the geographic impact of Daniel Sonntag's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Sonntag with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Sonntag more than expected).

Fields of papers citing papers by Daniel Sonntag

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Sonntag. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Sonntag. The network helps show where Daniel Sonntag may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel Sonntag, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Sonntag Line = papers co-authored together Daniel Sonntag links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 135 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202169
2 201537
3
LingInfo: Design and Applications of a Model for the Integration of Linguistic Information in Ontologies
200629
4 201429
5 201628
6 202227
7 201524
8 201823
9 201621
10 202120
11 202020
12 201519
13 201519
14 201418
15 200518
16
The Handbook of Multimodal-Multisensor Interfaces, Volume 1: Foundations, User Modeling, and Common Modality Combinations
201717
17 202116
18 201415
19 202114
20 201014

About Daniel Sonntag

Daniel Sonntag is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Human-Computer Interaction, Molecular Biology and Radiology, Nuclear Medicine and Imaging, having authored 135 papers that have together received 989 indexed citations. Recurring topics across this work include Gaze Tracking and Assistive Technology (30 papers), Topic Modeling (22 papers), Natural Language Processing Techniques (20 papers), Semantic Web and Ontologies (19 papers), Speech and dialogue systems (19 papers), Biomedical Text Mining and Ontologies (17 papers), Visual Attention and Saliency Detection (12 papers) and Augmented Reality Applications (10 papers). The work is most often cited by research in Human-Computer Interaction (357 citations), Health Informatics (57 citations), Computer Vision and Pattern Recognition (344 citations), Artificial Intelligence (325 citations) and Cognitive Neuroscience (124 citations). Daniel Sonntag has collaborated with scholars based in Germany, Hungary and Japan. Frequent co-authors include Michael Barz, Takumi Toyama, Jason Orlosky, Kiyoshi Kiyokawa, Jochen Kühn, Sebastian Kapp, Sonja Zillner, Markus Weber, Norbert Reithinger and Paul Buitelaar. Their work appears in journals such as Sensors, Scientific Reports, IEEE Transactions on Visualization and Computer Graphics, Ecological Informatics and Language Resources and Evaluation.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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