Maximilian Schmitt

2.2k citations
53 papers · 982 indexed · h-index 19
Topics
Emotion and Mood Recognition (20 papers)Music and Audio Processing (20 papers)Speech and Audio Processing (19 papers)

In The Last Decade

Maximilian Schmitt

52 papers receiving 937 citations

Peers

Maximilian Schmitt
Comparison fields: 5 of 106
  • Signal Processing 389
  • Experimental and Cognitive Psychology 375
  • Artificial Intelligence 369
  • Computer Vision and Pattern Recognition 135
  • Physiology 115
Replace Shahin Amiriparian with:
Shahin Amiriparian Germany
Alice Baird Germany
Hugues Salamin United Kingdom
Simone Hantke Germany
Maurice Gerczuk Germany
Tobias Bocklet Germany
Athanasios Katsamanis Greece
Fabio Valente Switzerland
Heysem Kaya Türkiye
Andreas Tsiartas United States
Maximilian Schmitt relative to Shahin Amiriparian Germany Shahin Amiriparian's profile →
Citations per field
00.5×1.5×
Shahin Amiriparian · 1×
Citations per year

Countries citing papers authored by Maximilian Schmitt

Since Specialization
Citations

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

Fields of papers citing papers by Maximilian Schmitt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maximilian Schmitt

This figure shows the co-authorship network connecting the top 25 collaborators of Maximilian Schmitt. A scholar is included among the top collaborators of Maximilian Schmitt 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 Maximilian Schmitt. Maximilian Schmitt 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
#WorkIndexed citations
1 4
2 5
3 10
4 18
5 1
6 16
7 20
8 8
9 25
10 1
11 5
12 12
13 4
14 4
15 62
16 35
17 3
18 5
19
A Bag-of-Audio-Words Approach for Snore Sounds' Excitation Localisation.
28
20
Towards Cross-lingual Automatic Diagnosis of Autism Spectrum Condition in Children's Voices.
8

About Maximilian Schmitt

Maximilian Schmitt is a scholar working on Signal Processing, Experimental and Cognitive Psychology and Artificial Intelligence, having authored 53 papers that have together received 982 indexed citations. Recurring topics across this work include Emotion and Mood Recognition (20 papers), Music and Audio Processing (20 papers) and Speech and Audio Processing (19 papers). The work is most often cited by research in Signal Processing (389 citations), Experimental and Cognitive Psychology (375 citations) and Artificial Intelligence (369 citations). Maximilian Schmitt has collaborated with scholars based in Germany, United Kingdom and Austria. Frequent co-authors include Björn W. Schuller, Fabien Ringeval, Jing Han, Shahin Amiriparian, Maja Pantić, Kun Qian, Nicholas Cummins, Vedhas Pandit, Zixing Zhang and Anton Batliner. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.

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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