Daniela Koller

103 papers receiving 3.2k citations

Peers

Daniela Koller
Comparison fields: 5 of 166
  • Immunology and Allergy 320
  • Geriatrics and Gerontology 117
  • Computer Vision and Pattern Recognition 455
  • Physiology 495
  • Epidemiology 600
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Michael J. Goodman United States
Yong Gyu Park South Korea
Shuyang Zhang China
Nicolas Molinari France
Yuliya Lokhnygina United States
François‐André Allaert France
Xingmei Wang China
Yanfeng Li China
Akbar K. Waljee United States
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Citations per year

Countries citing papers authored by Daniela Koller

Since Specialization
Citations

This map shows the geographic impact of Daniela Koller'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 Daniela Koller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniela Koller more than expected).

Fields of papers citing papers by Daniela Koller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniela Koller. 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 Daniela Koller. The network helps show where Daniela Koller may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniela Koller, 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 Daniela Koller Line = papers co-authored together Daniela Koller links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 110 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010305
2 2011268
3 2002266
4 2006224
5 2011109
6 2014104
7 2014100
8 199586
9
Automatic symbolic traffic scene analysis using belief networks
199485
10 199580
11 200276
12 199772
13 199171
14 199467
15 201658
16 199758
17 201557
18 201252
19 199951
20 201450

About Daniela Koller

Daniela Koller is a scholar working on General Health Professions, Epidemiology, Physiology, Public Health, Environmental and Occupational Health and Pulmonary and Respiratory Medicine, having authored 110 papers that have together received 3.4k indexed citations. Recurring topics across this work include Health and Medical Studies (16 papers), Chronic Disease Management Strategies (12 papers), Asthma and respiratory diseases (9 papers), Allergic Rhinitis and Sensitization (8 papers), Autonomous Vehicle Technology and Safety (5 papers), Pediatric health and respiratory diseases (5 papers), Vestibular and auditory disorders (5 papers) and Advanced Vision and Imaging (5 papers). The work is most often cited by research in Immunology and Allergy (320 citations), Geriatrics and Gerontology (117 citations), Computer Vision and Pattern Recognition (455 citations), Physiology (495 citations) and Epidemiology (600 citations). Daniela Koller has collaborated with scholars based in Germany, Austria and United States. Frequent co-authors include Gerd Glaeske, Hendrik van den Bussche, Gerhard Schön, Heike Hansen, R. Urbanek, Hanna Kaduszkiewicz, Karl Wegscheider, Jitendra Malik, Joseph Weber and Falk Hoffmann. Their work appears in journals such as Allergy, BMJ Open, American Journal of Respiratory and Critical Care Medicine, BMC Health Services Research and Archives of Disease in Childhood.

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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