Jan Lellmann

1.4k citations
39 papers · 766 · h-index 13

Impact in

Papers in

Jan Lellmann

34 papers receiving 724 citations

Peers

Jan Lellmann
Comparison fields: 5 of 89
  • Computer Vision and Pattern Recognition 447
  • Computer Graphics and Computer-Aided Design 39
  • Computational Mechanics 219
  • Mathematical Physics 71
  • Media Technology 54
Replace Egil Bae with:
Egil Bae Norway
Julien Rabin France
Andreas Weinmann Germany
Valérie Perrier France
Yen‐Hsi Richard Tsai United States
Bernhard Schmitzer Germany
François‐Xavier Vialard France
Seongjai Kim United States
Carlos Cabrelli Argentina
Florian Becker Germany
Jan Lellmann relative to Egil Bae Norway Egil Bae's profile →
Citations per field
00.5×1.5×2.2×
Egil Bae · 1×
Citations per year

Countries citing papers authored by Jan Lellmann

Since Specialization
Citations

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

Fields of papers citing papers by Jan Lellmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009112
2 2015108
3 201189
4 201461
5 201856
6 201655
7 200946
8 201340
9 201230
10 200824
11 202023
12 201019
13 201314
14 201312
15 201310
16 20129
17 20228
18 20147
19 20196
20 20116

About Jan Lellmann

Jan Lellmann is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Mathematical Physics, having authored 39 papers that have together received 766 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (17 papers), Sparse and Compressive Sensing Techniques (16 papers), Medical Imaging Techniques and Applications (6 papers), Advanced Vision and Imaging (5 papers), Image and Signal Denoising Methods (5 papers), Numerical methods in inverse problems (4 papers), Robotics and Sensor-Based Localization (3 papers) and Stochastic Gradient Optimization Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (447 citations), Computer Graphics and Computer-Aided Design (39 citations), Computational Mechanics (219 citations), Mathematical Physics (71 citations) and Media Technology (54 citations). Jan Lellmann has collaborated with scholars based in Germany, United Kingdom and France. Frequent co-authors include Christoph Schnörr, Florian Becker, Jörg Hendrik Kappes, Carola‐Bibiane Schönlieb, Jing Yuan, Frank Lenzen, Tuomo Valkonen, Dirk A. Lorenz, Evgeny Strekalovskiy and Daniel Cremers. Their work appears in journals such as SIAM Journal on Imaging Sciences, International Journal of Computer Vision, Journal of Mathematical Imaging and Vision, Lecture notes in computer science and IEEE Journal of Selected Topics in Applied Earth Observations 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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