Michael Wohlmayr
Impact in
- Signal Processing top 5%
- Speech and Audio Processing
- Music and Audio Processing
- Blind Source Separation Techniques
- Artificial Intelligence top 10%
- Speech Recognition and Synthesis
- Bayesian Modeling and Causal Inference
Papers in
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- Speech and Audio Processing 14
- Music and Audio Processing 12
- Blind Source Separation Techniques 3
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- Speech Recognition and Synthesis 7
- Bayesian Modeling and Causal Inference 2
- Machine Learning and Data Classification 2
- Bayesian Methods and Mixture Models 2
- Co-authors
- Franz Pernkopf (15 shared papers)Michael Stark (4 shared papers)Sebastian Tschiatschek (1 shared paper)Robert Peharz (2 shared papers)Maria Markaki (1 shared paper)
- Journals
- IEEE Transactions on Audio Speech and Language Processing (3 papers)Pattern Recognition (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)Zenodo (CERN European Organization for Nuclear Research) (1 paper)Cambridge University Engineering Department Publications Database (2 papers)
- Partner nations
- AustriaGermanyUnited States
In The Last Decade
Michael Wohlmayr
17 papers receiving 291 citations
Peers
Comparison fields: 5 of 38
- Signal Processing 244
- Artificial Intelligence 166
- Computational Mechanics 72
- Cognitive Neuroscience 28
- Computer Vision and Pattern Recognition 30
Countries citing papers authored by Michael Wohlmayr
This map shows the geographic impact of Michael Wohlmayr'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 Michael Wohlmayr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Wohlmayr more than expected).
Fields of papers citing papers by Michael Wohlmayr
This network shows the impact of papers produced by Michael Wohlmayr. 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 Michael Wohlmayr. The network helps show where Michael Wohlmayr may publish in the future.
Co-authors
The 5 scholars most cited alongside Michael Wohlmayr, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 90 | |
| 2 | 2010 | 49 | |
| 3 | 2010 | 46 | |
| 4 | 2011 | 31 | |
| 5 | 2012 | 27 | |
| 6 | 2007 | 18 | |
| 7 | 2007 | 14 | |
| 8 | 2013 | 6 | |
| 9 | 2009 | 5 | |
| 10 | 2011 | 5 | |
| 11 | 2011 | 3 | |
| 12 | 2011 | 3 | |
| 13 | 2008 | 3 | |
| 14 | 2010 | 2 | |
| 15 | 2014 | 2 | |
| 16 | 2010 | 1 | |
| 17 | 2007 | 1 |
About Michael Wohlmayr
Michael Wohlmayr is a scholar working on Signal Processing, Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mechanics and Developmental Biology, having authored 17 papers that have together received 306 indexed citations. Recurring topics across this work include Speech and Audio Processing (14 papers), Music and Audio Processing (12 papers), Speech Recognition and Synthesis (7 papers), Blind Source Separation Techniques (3 papers), Bayesian Modeling and Causal Inference (2 papers), Machine Learning and Data Classification (2 papers), Bayesian Methods and Mixture Models (2 papers) and Advanced Adaptive Filtering Techniques (2 papers). The work is most often cited by research in Signal Processing (244 citations), Artificial Intelligence (166 citations), Computational Mechanics (72 citations), Cognitive Neuroscience (28 citations) and Computer Vision and Pattern Recognition (30 citations). Michael Wohlmayr has collaborated with scholars based in Austria, Germany and United States. Frequent co-authors include Franz Pernkopf, Michael Stark, Sebastian Tschiatschek, Robert Peharz and Maria Markaki. Their work appears in journals such as IEEE Transactions on Audio Speech and Language Processing, Pattern Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, Zenodo (CERN European Organization for Nuclear Research) and Cambridge University Engineering Department Publications Database.
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.