B. Michaelis

954 citations
60 papers · 666 · h-index 14

Impact in

Papers in

B. Michaelis

57 papers receiving 604 citations

Peers

B. Michaelis
Comparison fields: 5 of 110
  • Virology 112
  • Computer Vision and Pattern Recognition 274
  • Media Technology 69
  • Infectious Diseases 130
  • Human-Computer Interaction 38
Replace Lijun Zhao with:
Lijun Zhao China
Xiangyun Liao China
A. Ravishankar Rao United States
Tianwei Lin China
Daniela Iacoviello Italy
Christopher E. Smith United States
David C. Gossard United States
Lili Wang China
Xuehua Li China
Qing Wei China
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Citations per field
00.5×4.2×
Lijun Zhao · 1×
Citations per year

Countries citing papers authored by B. Michaelis

Since Specialization
Citations

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

Fields of papers citing papers by B. Michaelis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1986180
2 201241
3 200236
4 197130
5 200225
6 200224
7 200924
8 200820
9 199819
10 200719
11 200218
12 200517
13 197315
14 200914
15 200612
16 199711
17 200211
18 199810
19 20029
20 20079

About B. Michaelis

B. Michaelis is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Cellular and Molecular Neuroscience, Cognitive Neuroscience and Artificial Intelligence, having authored 60 papers that have together received 666 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (11 papers), Video Surveillance and Tracking Methods (7 papers), Neural dynamics and brain function (7 papers), Robotics and Sensor-Based Localization (6 papers), Neural Networks and Applications (6 papers), Advanced Image Fusion Techniques (6 papers), Optical measurement and interference techniques (5 papers) and Image Enhancement Techniques (5 papers). The work is most often cited by research in Virology (112 citations), Computer Vision and Pattern Recognition (274 citations), Media Technology (69 citations), Infectious Diseases (130 citations) and Human-Computer Interaction (38 citations). B. Michaelis has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Pedro Albrecht, R. A. Chaplain, JayA. Levy, Ayoub Al-Hamadi, Hamid R. Tizhoosh, Gerald Krell, Robert Niese, R. Coenen, Aly A. Farag and Heiko Neumann. Their work appears in journals such as International Journal of Medical Informatics, International Journal of Heat and Mass Transfer, Journal of Medical Systems, Mathematical Biosciences and ISPRS Journal of Photogrammetry and Remote Sensing.

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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