Klaus U. Schulz

2.0k citations
65 papers · 704 · h-index 15

Impact in

Papers in

Klaus U. Schulz

61 papers receiving 594 citations

Peers

Klaus U. Schulz
Comparison fields: 5 of 70
  • Artificial Intelligence 539
  • Computational Theory and Mathematics 143
  • Signal Processing 91
  • Computer Vision and Pattern Recognition 140
  • Computer Networks and Communications 154
Replace Mehrnoush Shamsfard with:
Mehrnoush Shamsfard Iran
Marc Vilain United States
Shankar Kumar United States
Sebastian Maneth Germany
Alessandro Artale Italy
Ralph E. Griswold United States
Sujith Ravi United States
Doug Cutting United States
Kurt Maly United States
Bart Bogaerts Belgium
Klaus U. Schulz relative to Mehrnoush Shamsfard Iran Mehrnoush Shamsfard's profile →
Citations per field
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Mehrnoush Shamsfard · 1×
Citations per year

Countries citing papers authored by Klaus U. Schulz

Since Specialization
Citations

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

Fields of papers citing papers by Klaus U. Schulz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Klaus U. Schulz. 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 Klaus U. Schulz. The network helps show where Klaus U. Schulz may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 65 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002116
2 199645
3 200440
4 200638
5 200433
6 200632
7 201028
8 200723
9 200923
10 201020
11 200519
12 200218
13 199617
14 199317
15 200914
16 201414
17 200113
18 200413
19 200512
20 200711

About Klaus U. Schulz

Klaus U. Schulz is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Computer Networks and Communications and Signal Processing, having authored 65 papers that have together received 704 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (24 papers), Algorithms and Data Compression (20 papers), Handwritten Text Recognition Techniques (13 papers), Advanced Database Systems and Queries (11 papers), Data Management and Algorithms (9 papers), semigroups and automata theory (8 papers), Semantic Web and Ontologies (7 papers) and Logic, programming, and type systems (6 papers). The work is most often cited by research in Artificial Intelligence (539 citations), Computational Theory and Mathematics (143 citations), Signal Processing (91 citations), Computer Vision and Pattern Recognition (140 citations) and Computer Networks and Communications (154 citations). Klaus U. Schulz has collaborated with scholars based in Germany, Bulgaria and United States. Frequent co-authors include Stoyan Mihov, Franz Baader, Georg Gottlob, Christoph Koch, Holger Meuss, Andreas Neumann, Manfred Schmidt-Schauß, Paul Buitelaar, François Bry and Elisabeth Leiss. Their work appears in journals such as International Journal on Document Analysis and Recognition (IJDAR), Theoretical Computer Science, Natural Language Engineering, Computational Linguistics and ACM Transactions on Information Systems.

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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