S. Baumann

1.6k citations
47 papers · 437 · h-index 13

Impact in

Papers in

S. Baumann

43 papers receiving 371 citations

Peers

S. Baumann
Comparison fields: 5 of 70
  • Signal Processing 208
  • Computer Vision and Pattern Recognition 195
  • Human-Computer Interaction 23
  • Information Systems 90
  • Artificial Intelligence 128
Replace Shannon Bradshaw with:
Shannon Bradshaw United States
Ziyi Kou United States
Ron Davidson United States
S. R. Subramanya United States
Beth Hetzler United States
Utz Westermann Austria
Assef Jafar Syria
Aakarsh Malhotra India
John Wenskovitch United States
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Citations per field
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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 25 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 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200570
2 200443
3
Exploiting immunology and molecular genetics for rational vaccine design against tuberculosis.
200640
4 200725
5 200522
6
TOWARDS A SOCIO-CULTURAL COMPATIBILITY OF MIR SYSTEMS
200417
7 200217
8 200217
9 200213
10 199813
11 200313
12 201012
13 200312
14 200510
15
AN ECOLOGICAL APPROACH TO MULTIMODAL SUBJECTIVE MUSIC SIMILARITY PERCEPTION
20049
16 20088
17 20127
18 20107
19 20097
20 20156

About S. Baumann

S. Baumann is a scholar working on Signal Processing, Information Systems, Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications, having authored 47 papers that have together received 437 indexed citations. Recurring topics across this work include Music and Audio Processing (13 papers), Music Technology and Sound Studies (10 papers), Complex Network Analysis Techniques (6 papers), Web Data Mining and Analysis (5 papers), Handwritten Text Recognition Techniques (4 papers), Data Management and Algorithms (4 papers), Advanced Database Systems and Queries (4 papers) and Recommender Systems and Techniques (4 papers). The work is most often cited by research in Signal Processing (208 citations), Computer Vision and Pattern Recognition (195 citations), Human-Computer Interaction (23 citations), Information Systems (90 citations) and Artificial Intelligence (128 citations). S. Baumann has collaborated with scholars based in Germany, Netherlands and France. Frequent co-authors include Shankar Vembu, Oliver Hummel, Stefan H. E. Kaufmann, Ali Nasser Eddine, Andreas Dengel, C. Wenzel, Tim Pohle, Andreas Dengel, John Halloran and Kai-Uwe Sattler. Their work appears in journals such as Blood, Journal of New Music Research, Distributed and Parallel Databases, Social Network Analysis and Mining and Lecture notes in computer science.

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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