Dagmar Schuller

592 total citations
13 papers, 296 citations indexed

About

Dagmar Schuller is a scholar working on Signal Processing, Experimental and Cognitive Psychology and Artificial Intelligence. According to data from OpenAlex, Dagmar Schuller has authored 13 papers receiving a total of 296 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Signal Processing, 5 papers in Experimental and Cognitive Psychology and 4 papers in Artificial Intelligence. Recurrent topics in Dagmar Schuller's work include Music and Audio Processing (6 papers), Emotion and Mood Recognition (5 papers) and Speech and Audio Processing (4 papers). Dagmar Schuller is often cited by papers focused on Music and Audio Processing (6 papers), Emotion and Mood Recognition (5 papers) and Speech and Audio Processing (4 papers). Dagmar Schuller collaborates with scholars based in Germany, United Kingdom and United States. Dagmar Schuller's co-authors include Björn W. Schuller, Florian Eyben, Xiao Li, Gerhard Rigoll, Kun Qian, Huaiyuan Zheng, Juan Liu, Jun Deng, Zixing Zhang and Eunmi Oh and has published in prestigious journals such as Computer, IEEE Transactions on Intelligent Transportation Systems and Neural Computing and Applications.

In The Last Decade

Dagmar Schuller

13 papers receiving 278 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dagmar Schuller Germany 8 103 101 80 47 44 13 296
Georgios Rizos United Kingdom 10 92 0.9× 173 1.7× 66 0.8× 38 0.8× 16 0.4× 21 305
Lukas Stappen Germany 12 117 1.1× 261 2.6× 249 3.1× 73 1.6× 38 0.9× 25 516
Emilia Parada‐Cabaleiro Germany 12 203 2.0× 225 2.2× 115 1.4× 86 1.8× 84 1.9× 43 502
Aseel Alhadlaq Saudi Arabia 6 73 0.7× 86 0.9× 98 1.2× 37 0.8× 23 0.5× 9 260
Dominik Schiller Germany 10 56 0.5× 165 1.6× 49 0.6× 58 1.2× 27 0.6× 25 331
Min Ma China 11 87 0.8× 235 2.3× 35 0.4× 13 0.3× 36 0.8× 32 352
Asif Salekin United States 8 30 0.3× 118 1.2× 71 0.9× 26 0.6× 28 0.6× 34 345
Thomas Polzin United States 10 201 2.0× 294 2.9× 286 3.6× 137 2.9× 44 1.0× 13 543
Félix Fuentes-Hurtado Spain 8 35 0.3× 73 0.7× 70 0.9× 68 1.4× 87 2.0× 15 309
Olivier Deroo Belgium 9 259 2.5× 375 3.7× 110 1.4× 68 1.4× 31 0.7× 19 517

Countries citing papers authored by Dagmar Schuller

Since Specialization
Citations

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

Fields of papers citing papers by Dagmar Schuller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dagmar Schuller

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

All Works

13 of 13 papers shown
1.
Reichel, Uwe D., Robert Hoepner, Hesam Sagha, et al.. (2023). Towards Supporting an Early Diagnosis of Multiple Sclerosis using Vocal Features. OPUS (Augsburg University). 1518–1522. 1 indexed citations
2.
Schuller, Dagmar, et al.. (2023). Audiovisual Affect Recognition for Autonomous Vehicles: Applications and Future Agendas. IEEE Transactions on Intelligent Transportation Systems. 25(6). 4918–4932. 3 indexed citations
3.
Schuller, Björn W., Dagmar Schuller, Kun Qian, et al.. (2021). COVID-19 and Computer Audition: An Overview on What Speech & Sound Analysis Could Contribute in the SARS-CoV-2 Corona Crisis. Frontiers in Digital Health. 3. 564906–564906. 49 indexed citations
4.
Pokorny, Florian B., Katrin D. Bartl-Pokorny, Uwe D. Reichel, et al.. (2021). Speaking Corona? Human and Machine Recognition of COVID-19 from Voice. OPUS (Augsburg University). 1029–1033. 4 indexed citations
5.
Pokorny, Florian B., Katrin D. Bartl-Pokorny, Dajie Zhang, et al.. (2020). Efficient Collection and Representation of Preverbal Data in Typical and Atypical Development. Journal of Nonverbal Behavior. 44(4). 419–436. 7 indexed citations
6.
Schuller, Dagmar & Björn W. Schuller. (2020). A Review on Five Recent and Near-Future Developments in Computational Processing of Emotion in the Human Voice. Emotion Review. 13(1). 44–50. 35 indexed citations
7.
Deng, Jun, Björn W. Schuller, Florian Eyben, et al.. (2019). Exploiting time-frequency patterns with LSTM-RNNs for low-bitrate audio restoration. Neural Computing and Applications. 32(4). 1095–1107. 33 indexed citations
8.
Schuller, Dagmar & Björn W. Schuller. (2018). The Age of Artificial Emotional Intelligence. Computer. 51(9). 38–46. 69 indexed citations
9.
Eyben, Florian, et al.. (2017). VoicePlay — An affective sports game operated by speech emotion recognition based on the component process model. OPUS (Augsburg University). 74–76. 4 indexed citations
10.
Schuller, Dagmar, et al.. (2015). Cross-language acoustic emotion recognition: An overview and some tendencies. 125–131. 42 indexed citations
11.
Eyben, Florian, Bernd Huber, Erik Marchi, Dagmar Schuller, & Björn W. Schuller. (2015). Real-time robust recognition of speakers' emotions and characteristics on mobile platforms. OPUS (Augsburg University). 6. 778–780. 9 indexed citations
12.
Schuller, Björn W., et al.. (2010). ‘Mister D.J., Cheer Me Up!’:Musical and Textual Features for Automatic Mood Classification. Journal of New Music Research. 39(1). 13–34. 31 indexed citations
13.
Heß, Thomas & Dagmar Schuller. (2005). Business Process Reengineering als nachhaltiger Trend? Eine Analyse der Praxis in deutschen Großunternehmen nach einer Dekade. Schmalenbach Journal of Business Research. 57(4). 355–373. 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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2026