S. Baumann

1.3k citations
73 papers · 977 · h-index 17

Impact in

Papers in

S. Baumann

71 papers receiving 886 citations

Peers

S. Baumann
Comparison fields: 5 of 29
  • Nuclear and High Energy Physics 475
  • Signal Processing 118
  • Artificial Intelligence 88
  • Computer Vision and Pattern Recognition 63
  • Information Systems 55
Replace J. Y. Shi with:
J. Y. Shi China
Gaurav Goswami India
X. D. Zhang United States
Shigeru Nakayama Japan
Daehyeok Kim United States
Jose Ignacio Martin Spain
William Caelli Australia
Mohammed Bakiri Algeria
Sean D. Ahern United States
Basanta Joshi India
S. Baumann relative to J. Y. Shi China J. Y. Shi's profile →
Citations per field
00.5×2×3.4×
J. Y. Shi · 1×
Citations per year

Countries citing papers authored by S. Baumann

Since Specialization
Citations

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

Fields of papers citing papers by S. Baumann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 11 scholars most cited alongside S. Baumann, 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 S. Baumann Line = papers co-authored together S. Baumann links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 73 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200777
2 200573
3 200444
4 199940
5 200032
6 199831
7 200031
8 199730
9 200030
10 199829
11 199827
12 199926
13 198724
14 199824
15 200724
16 200723
17 200520
18 200217
19 200217
20
TOWARDS A SOCIO-CULTURAL COMPATIBILITY OF MIR SYSTEMS
200416

About S. Baumann

S. Baumann is a scholar working on Nuclear and High Energy Physics, Signal Processing, Information Systems, Artificial Intelligence and Statistical and Nonlinear Physics, having authored 73 papers that have together received 977 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (35 papers), Recommender Systems and Techniques (7 papers), Music and Audio Processing (6 papers), Semantic Web and Ontologies (4 papers), Sentiment Analysis and Opinion Mining (3 papers), Handwritten Text Recognition Techniques (2 papers), Complex Network Analysis Techniques (2 papers) and Particle Detector Development and Performance (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (475 citations), Signal Processing (118 citations), Artificial Intelligence (88 citations), Computer Vision and Pattern Recognition (63 citations) and Information Systems (55 citations). S. Baumann has collaborated with scholars based in Germany, United Kingdom and Switzerland. Frequent co-authors include Shankar Vembu, Oliver Hummel, Andreas Dengel, Andreas Dengel, Tim Pohle, Stefan Agne, Thomas Kieninger, Rainer Hoch, Norbert Kühn and Markus Junker. Their work appears in journals such as Physics Letters B, The European Physical Journal C, Journal of Web Semantics, Journal of New Music Research and Social Network Analysis and Mining.

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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