Jan Lellmann

1.4k citations
24 papers · 477 · h-index 11

Impact in

Papers in

Jan Lellmann

20 papers receiving 457 citations

Peers

Jan Lellmann
Comparison fields: 5 of 83
  • Computer Vision and Pattern Recognition 226
  • Computational Mechanics 107
  • Computational Mathematics 3
  • Mathematical Physics 43
  • Computer Graphics and Computer-Aided Design 16
Replace Andreas Weinmann with:
Andreas Weinmann Germany
Bernhard Schmitzer Germany
François‐Xavier Vialard France
Mauro Piccioni Italy
Arjuna Flenner United States
Julien Rabin France
Jeff Calder United States
Lénaïc Chizat France
Seongjai Kim United States
Huiling Le United Kingdom
Jan Lellmann relative to Andreas Weinmann Germany Andreas Weinmann's profile →
Citations per field
00.5×1.5×
Andreas Weinmann · 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 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201579
2 201167
3 201855
4 201454
5 201653
6 200932
7 201329
8 201226
9 200821
10 202020
11 201310
12 20127
13 20226
14 20145
15 20234
16 20223
17 20243
18 20231
19 20111
20 20111

About Jan Lellmann

Jan Lellmann is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Molecular Biology, having authored 24 papers that have together received 477 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (8 papers), Sparse and Compressive Sensing Techniques (8 papers), Medical Imaging Techniques and Applications (3 papers), Stochastic Gradient Optimization Techniques (3 papers), Image and Signal Denoising Methods (3 papers), Optical measurement and interference techniques (2 papers), Numerical methods in inverse problems (2 papers) and Quantum Computing Algorithms and Architecture (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (226 citations), Computational Mechanics (107 citations), Computational Mathematics (3 citations), Mathematical Physics (43 citations) and Computer Graphics and Computer-Aided Design (16 citations). Jan Lellmann has collaborated with scholars based in Germany, United Kingdom and Sweden. Frequent co-authors include Christoph Schnörr, Carola‐Bibiane Schönlieb, Florian Becker, Tuomo Valkonen, Dirk A. Lorenz, Frank Lenzen, Evgeny Strekalovskiy, Daniel Cremers, Nathalie Butt and Michele Dalponte. Their work appears in journals such as SIAM Journal on Imaging Sciences, International Journal of Computer Vision, Journal of Mathematical Imaging and Vision, PROTEOMICS - CLINICAL APPLICATIONS and Quantum Information Processing.

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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