Christoph Janott

530 total citations
14 papers, 306 citations indexed

About

Christoph Janott is a scholar working on Signal Processing, Physiology and Automotive Engineering. According to data from OpenAlex, Christoph Janott has authored 14 papers receiving a total of 306 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Signal Processing, 9 papers in Physiology and 3 papers in Automotive Engineering. Recurrent topics in Christoph Janott's work include Speech and Audio Processing (10 papers), Obstructive Sleep Apnea Research (9 papers) and Music and Audio Processing (8 papers). Christoph Janott is often cited by papers focused on Speech and Audio Processing (10 papers), Obstructive Sleep Apnea Research (9 papers) and Music and Audio Processing (8 papers). Christoph Janott collaborates with scholars based in Germany, United Kingdom and Japan. Christoph Janott's co-authors include Björn W. Schuller, Clemens Heiser, Kun Qian, Zixing Zhang, Werner Hemmert, Winfried Hohenhorst, Michael Herzog, Maximilian Schmitt, Vedhas Pandit and Jing Han and has published in prestigious journals such as IEEE Transactions on Biomedical Engineering, Annals of Biomedical Engineering and Computers in Biology and Medicine.

In The Last Decade

Christoph Janott

14 papers receiving 300 citations

Peers

Christoph Janott
Christoph Janott
Citations per year, relative to Christoph Janott Christoph Janott (= 1×) peers January Gnitecki

Countries citing papers authored by Christoph Janott

Since Specialization
Citations

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

Fields of papers citing papers by Christoph Janott

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Christoph Janott

This figure shows the co-authorship network connecting the top 25 collaborators of Christoph Janott. A scholar is included among the top collaborators of Christoph Janott 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 Christoph Janott. Christoph Janott is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Qian, Kun, Christoph Janott, Maximilian Schmitt, et al.. (2020). Can Machine Learning Assist Locating the Excitation of Snore Sound? A Review. IEEE Journal of Biomedical and Health Informatics. 25(4). 1233–1246. 25 indexed citations
2.
Janott, Christoph, Maximilian Schmitt, Clemens Heiser, et al.. (2019). VOTE versus ACLTE: Vergleich zweier Schnarchgeräuschklassifikationen mit Methoden des maschinellen Lernens. HNO. 67(9). 670–678. 5 indexed citations
3.
Janott, Christoph, Christian Rohrmeier, Maximilian Schmitt, Werner Hemmert, & Björn W. Schuller. (2019). Snoring - An Acoustic Definition. PubMed. 68. 3653–3657. 4 indexed citations
4.
Qian, Kun, Maximilian Schmitt, Christoph Janott, et al.. (2019). A Bag of Wavelet Features for Snore Sound Classification. Annals of Biomedical Engineering. 47(4). 1000–1011. 29 indexed citations
5.
Zhang, Zixing, Jing Han, Kun Qian, et al.. (2019). Snore-GANs: Improving Automatic Snore Sound Classification With Synthesized Data. IEEE Journal of Biomedical and Health Informatics. 24(1). 300–310. 46 indexed citations
6.
Qian, Kun, Christoph Janott, Zixing Zhang, et al.. (2018). Teaching Machines on Snoring: A Benchmark on Computer Audition for Snore Sound Excitation Localisation. Archives of Acoustics. 465–475. 11 indexed citations
7.
Janott, Christoph, Maximilian Schmitt, Kun Qian, et al.. (2018). Snoring classified: The Munich-Passau Snore Sound Corpus. Computers in Biology and Medicine. 94. 106–118. 35 indexed citations
8.
Janott, Christoph, Björn W. Schuller, & Clemens Heiser. (2017). Akustische Informationen von Schnarchgeräuschen. HNO. 65(2). 107–116. 12 indexed citations
9.
Qian, Kun, Christoph Janott, Jun Deng, et al.. (2017). Snore sound recognition: On wavelets and classifiers from deep nets to kernels. PubMed. 11. 3737–3740. 15 indexed citations
10.
Schmitt, Maximilian, Christoph Janott, Vedhas Pandit, et al.. (2016). A Bag-of-Audio-Words Approach for Snore Sounds' Excitation Localisation.. OPUS (Augsburg University). 230–234. 28 indexed citations
11.
Qian, Kun, Christoph Janott, Vedhas Pandit, et al.. (2016). Classification of the Excitation Location of Snore Sounds in the Upper Airway by Acoustic Multifeature Analysis. IEEE Transactions on Biomedical Engineering. 64(8). 1731–1741. 61 indexed citations
12.
Qian, Kun, Christoph Janott, Zixing Zhang, Clemens Heiser, & Björn W. Schuller. (2016). Wavelet features for classification of vote snore sounds. OPUS (Augsburg University). 221–225. 25 indexed citations
13.
Guo, Jian, et al.. (2016). GPU-based fast signal processing for large amounts of snore sound data. OPUS (Augsburg University). 1–2. 1 indexed citations
14.
Janott, Christoph, W. Pirsig, & Clemens Heiser. (2014). Akustische Analyse von Schnarchgeräuschen. Somnologie - Schlafforschung und Schlafmedizin. 18(2). 87–95. 9 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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