Stefan Uhlich

1.0k citations
33 papers · 501 · h-index 10

Impact in

Papers in

Stefan Uhlich

29 papers receiving 459 citations

Peers

Stefan Uhlich
Comparison fields: 5 of 53
  • Signal Processing 391
  • Computer Vision and Pattern Recognition 127
  • Artificial Intelligence 164
  • Computational Mechanics 60
  • Music 6
Replace R. Coelho with:
R. Coelho Brazil
Ramón Fernández Astudillo Portugal
E. Shlomot United States
Hossein Sameti Iran
Kazuhito Koishida United States
Biing Hwang Juang United States
Yuxuan Wang China
Steven Lauwereins Belgium
Stylianos Moschoglou United Kingdom
Claude Lamblin France
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Citations per field
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Citations per year

Countries citing papers authored by Stefan Uhlich

Since Specialization
Citations

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

Fields of papers citing papers by Stefan Uhlich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019139
2 2017106
3 201568
4 202238
5 200918
6 201917
7 201517
8
Differentiable Quantization of Deep Neural Networks.
201915
9 201913
10 202012
11 20238
12 20246
13 20156
14
Music Demixing Challenge at ISMIR 2021.
20214
15 20104
16 20094
17 20224
18 20093
19 20233
20 20242

About Stefan Uhlich

Stefan Uhlich is a scholar working on Signal Processing, Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mechanics and Control and Systems Engineering, having authored 33 papers that have together received 501 indexed citations. Recurring topics across this work include Speech and Audio Processing (17 papers), Music and Audio Processing (12 papers), Music Technology and Sound Studies (6 papers), Blind Source Separation Techniques (6 papers), Advanced Adaptive Filtering Techniques (6 papers), Speech Recognition and Synthesis (6 papers), Control Systems and Identification (4 papers) and Advanced Statistical Methods and Models (2 papers). The work is most often cited by research in Signal Processing (391 citations), Computer Vision and Pattern Recognition (127 citations), Artificial Intelligence (164 citations), Computational Mechanics (60 citations) and Music (6 citations). Stefan Uhlich has collaborated with scholars based in Germany, United States and Japan. Frequent co-authors include Yuki Mitsufuji, Fabian-Robert Stöter, Franck Giron, Antoine Liutkus, Thomas Kemp, Naoya Takahashi, Bin Yang, Fabien Cardinaux, Akira Nakamura and Lukas Mauch. Their work appears in journals such as IEEE Transactions on Signal Processing, IEEE/ACM Transactions on Audio Speech and Language Processing, IEEE Signal Processing Letters, IEEE Journal of Selected Topics in Signal Processing and EURASIP Journal on Audio Speech and Music 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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