Carsten Gottschlich

767 citations
20 papers · 445 · h-index 11

Impact in

Papers in

Carsten Gottschlich

20 papers receiving 428 citations

Peers

Carsten Gottschlich
Comparison fields: 5 of 86
  • Signal Processing 291
  • Safety Research 129
  • Computer Vision and Pattern Recognition 216
  • Biophysics 18
  • Cell Biology 47
Replace Fouad Khelifi with:
Fouad Khelifi United Kingdom
Mahdi S. Hosseini Canada
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Aditya Ramesh United States
Aakarsh Malhotra India
Huihui Wu Canada
Peipeng Yu China
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Citations per field
00.5×10×15×18.4×
Fouad Khelifi · 1×
Citations per year

Countries citing papers authored by Carsten Gottschlich

Since Specialization
Citations

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

Fields of papers citing papers by Carsten Gottschlich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Carsten Gottschlich, 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 Carsten Gottschlich Line = papers co-authored together Carsten Gottschlich links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201190
2 201461
3 201557
4 201241
5 200938
6 201129
7 201427
8 201625
9 201420
10 201616
11 201610
12 20196
13 20195
14 20165
15 20155
16 20153
17
Computation of Optimal Transport Plans and Wasserstein Distances [R package transport version 0.12-2]
20203
18
Statistical Analyses of Fingerprint Growth.
20112
19 20091
20 20151

About Carsten Gottschlich

Carsten Gottschlich is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Safety Research, Genetics and Organic Chemistry, having authored 20 papers that have together received 445 indexed citations. Recurring topics across this work include Biometric Identification and Security (14 papers), Forensic Fingerprint Detection Methods (5 papers), Forensic and Genetic Research (3 papers), Wood and Agarwood Research (2 papers), Advanced Steganography and Watermarking Techniques (2 papers), Cellular Mechanics and Interactions (2 papers), Automated Road and Building Extraction (2 papers) and Face recognition and analysis (2 papers). The work is most often cited by research in Signal Processing (291 citations), Safety Research (129 citations), Computer Vision and Pattern Recognition (216 citations), Biophysics (18 citations) and Cell Biology (47 citations). Carsten Gottschlich has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Stephan Huckemann, Carola‐Bibiane Schönlieb, Dominic Schuhmacher, Axel Munk, Emanuela Marasco, Allen Y. Yang, Bojan Čukić, Preda Mihăilescu, Florian Rehfeldt and Carina Wollnik. Their work appears in journals such as PLoS ONE, IEEE Transactions on Information Forensics and Security, Journal of Mathematical Biology, IEEE Transactions on Image Processing and IEEE Access.

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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