Peter Beyerlein

1.1k total citations
47 papers, 790 citations indexed

About

Peter Beyerlein is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Peter Beyerlein has authored 47 papers receiving a total of 790 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 17 papers in Signal Processing and 13 papers in Computer Vision and Pattern Recognition. Recurrent topics in Peter Beyerlein's work include Speech Recognition and Synthesis (17 papers), Speech and Audio Processing (13 papers) and Music and Audio Processing (8 papers). Peter Beyerlein is often cited by papers focused on Speech Recognition and Synthesis (17 papers), Speech and Audio Processing (13 papers) and Music and Audio Processing (8 papers). Peter Beyerlein collaborates with scholars based in Germany, United States and Finland. Peter Beyerlein's co-authors include Chamindie Punyadeera, Justin J. Cooper‐White, Karam Kostner, Goce Dimeski, Reinhold Haeb‐Umbach, Jeremy Chien, Andreas S. Beutler, Michaela S. Banck, Xavier Aubert and Bill Byrne and has published in prestigious journals such as Nucleic Acids Research, Annals of Neurology and Scientific Reports.

In The Last Decade

Peter Beyerlein

45 papers receiving 719 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Peter Beyerlein Germany 15 311 214 176 90 83 47 790
Florian Kraft Germany 16 176 0.6× 135 0.6× 241 1.4× 42 0.5× 35 0.4× 45 779
Jinyuan He China 15 72 0.2× 47 0.2× 88 0.5× 65 0.7× 49 0.6× 45 573
Asif Javed United States 13 78 0.3× 55 0.3× 215 1.2× 52 0.6× 55 0.7× 43 733
Andreas M. Kist Germany 16 125 0.4× 31 0.1× 185 1.1× 34 0.4× 9 0.1× 44 760
Hiroshi Higashi Japan 22 40 0.1× 165 0.8× 116 0.7× 117 1.3× 49 0.6× 79 1.0k
Xiao Lei Zhang China 11 48 0.2× 51 0.2× 88 0.5× 102 1.1× 35 0.4× 19 607
Marc Silverman United States 10 25 0.1× 99 0.5× 64 0.4× 102 1.1× 17 0.2× 19 704
Son Nguyen Vietnam 12 70 0.2× 78 0.4× 482 2.7× 29 0.3× 110 1.3× 33 980
Julia Lasserre Germany 8 132 0.4× 29 0.1× 646 3.7× 24 0.3× 135 1.6× 9 941

Countries citing papers authored by Peter Beyerlein

Since Specialization
Citations

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

Fields of papers citing papers by Peter Beyerlein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Beyerlein

This figure shows the co-authorship network connecting the top 25 collaborators of Peter Beyerlein. A scholar is included among the top collaborators of Peter Beyerlein based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Peter Beyerlein. Peter Beyerlein is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Beyerlein, Peter, et al.. (2024). Quantitative determination of dopamine in the presence of interfering substances supported by machine learning tools. Bioelectrochemistry. 157. 108667–108667. 3 indexed citations
2.
Schilling, Vincent, Peter Beyerlein, & Jeremy Chien. (2023). A Bioinformatics Analysis of Ovarian Cancer Data Using Machine Learning. Algorithms. 16(7). 330–330. 6 indexed citations
3.
Meier, Richard, Stefan Graw, Peter Beyerlein, et al.. (2017). digit—a tool fordetection andidentification ofgenomicinterchromosomaltranslocations. Nucleic Acids Research. 45(9). gkx010–gkx010. 1 indexed citations
4.
Graw, Stefan, Richard Meier, Kay Minn, et al.. (2015). Robust gene expression and mutation analyses of RNA-sequencing of formalin-fixed diagnostic tumor samples. Scientific Reports. 5(1). 12335–12335. 53 indexed citations
5.
Kulkarni, Amit, Rahul Kanwar, Peter Beyerlein, et al.. (2015). Association of the Charcot–Marie–Tooth disease gene ARHGEF10 with paclitaxel induced peripheral neuropathy in NCCTG N08CA (Alliance). Journal of the Neurological Sciences. 357(1-2). 35–40. 39 indexed citations
6.
Munchel, Sarah, Yue Zhao, Brandy Klotzle, et al.. (2015). Targeted or whole genome sequencing of formalin fixed tissue samples: potential applications in cancer genomics. Oncotarget. 6(28). 25943–25961. 46 indexed citations
7.
Mitrović, J., Christin Siewert, Bojan Duduk, et al.. (2013). Generation and Analysis of Draft Sequences of ‘Stolbur' Phytoplasma from Multiple Displacement Amplification Templates. Microbial Physiology. 24(1). 1–11. 27 indexed citations
8.
Bülow, Thomas, et al.. (2012). A multi-dimensional model for localization of highly variable objects. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8314. 83142L–83142L. 2 indexed citations
9.
Lorenz, Christian D., et al.. (2011). Discriminative Generalized Hough Transform for Localization of Lower Limbs. Computer Science - Research and Development. 2 indexed citations
10.
Punyadeera, Chamindie, Goce Dimeski, Karam Kostner, Peter Beyerlein, & Justin J. Cooper‐White. (2011). One-step homogeneous C-reactive protein assay for saliva. Journal of Immunological Methods. 373(1-2). 19–25. 96 indexed citations
11.
Wang, Chong, et al.. (2011). An Efficient Method for Modeling Kinetic Behavior of Channel Proteins in Cardiomyocytes. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 9(1). 40–51.
12.
Lorenz, Cristian, et al.. (2010). Fully Automatic Model Creation for Object Localization utilizing the Generalized Hough Transform.. 281–285. 6 indexed citations
13.
Lorenz, Cristian, et al.. (2010). Lokalisierung der Leber mittels einer Diskriminativen Generalisierten Hough Transformation. 183–188. 1 indexed citations
14.
Beyerlein, Peter, et al.. (2010). Interplay of potassium channels in modulating the action potential of the human left ventricle. Computing in Cardiology. 653–656. 1 indexed citations
15.
Lorenz, Christian D., et al.. (2010). Discriminative Generalized Hough transform for localization of joints in the lower extremities. Computer Science - Research and Development. 26(1-2). 97–105. 13 indexed citations
16.
Meyer, Carsten & Peter Beyerlein. (2002). Towards Large Margin Speech Recognizers by Boosting and Discriminative Training. International Conference on Machine Learning. 419–426. 2 indexed citations
17.
Beyerlein, Peter. (2002). Discriminative model combination. 1. 481–484. 69 indexed citations
18.
Haeb‐Umbach, Reinhold, et al.. (2002). Automatic transcription of unknown words in a speech recognition system. 1. 840–843. 12 indexed citations
19.
Beyerlein, Peter, et al.. (2001). Towards discriminative lexicon optimization. 1457–1460. 1 indexed citations
20.
Beyerlein, Peter, Xavier Aubert, Reinhold Haeb‐Umbach, et al.. (1999). The philips/RWTH system for transcription of broadcast news. 647–650. 13 indexed citations

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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