Michael Glodek

707 citations
17 papers · 244 · h-index 10

Impact in

Papers in

    • Neural Networks and Applications 3
    • Anomaly Detection Techniques and Applications 3
    • Bayesian Modeling and Causal Inference 2
    • Speech and Audio Processing 6
    • Music and Audio Processing 4

Michael Glodek

16 papers receiving 228 citations

Peers

Michael Glodek
Comparison fields: 5 of 52
  • Experimental and Cognitive Psychology 108
  • Signal Processing 68
  • Human-Computer Interaction 26
  • Artificial Intelligence 127
  • Computer Vision and Pattern Recognition 61
Replace Martin Schels with:
Martin Schels Germany
Ingo Siegert Germany
Ronald Böck Germany
Linlin Chao China
Değer Ayata Türkiye
Shamane Siriwardhana New Zealand
Kalin Stefanov Australia
Licai Sun China
Changzeng Fu Japan
Michael Glodek relative to Martin Schels Germany Martin Schels's profile →
Citations per field
00.5×1.5×2.4×
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Citations per year

Countries citing papers authored by Michael Glodek

Since Specialization
Citations

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

Fields of papers citing papers by Michael Glodek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Michael Glodek, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael Glodek Line = papers co-authored together Michael Glodek links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 201451
2 201230
3 201227
4 201221
5 201321
6 201521
7 201114
8 201112
9 201212
10 201111
11 20139
12 20145
13 20133
14 20133
15 20132
16 20131
17 20141

About Michael Glodek

Michael Glodek is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Cognitive Neuroscience, having authored 17 papers that have together received 244 indexed citations. Recurring topics across this work include Speech and Audio Processing (6 papers), Face and Expression Recognition (5 papers), Music and Audio Processing (4 papers), Video Surveillance and Tracking Methods (3 papers), Neural Networks and Applications (3 papers), Emotion and Mood Recognition (3 papers), Anomaly Detection Techniques and Applications (3 papers) and Bayesian Modeling and Causal Inference (2 papers). The work is most often cited by research in Experimental and Cognitive Psychology (108 citations), Signal Processing (68 citations), Human-Computer Interaction (26 citations), Artificial Intelligence (127 citations) and Computer Vision and Pattern Recognition (61 citations). Michael Glodek has collaborated with scholars based in Germany, Italy and Ireland. Frequent co-authors include Friedhelm Schwenker, Martin Schels, Günther Palm, Stefan Scherer, Markus Kächele, Nick Campbell, Steffen Walter, Georg Layher, Stephan Tschechne and Tobias Brosch. Their work appears in journals such as ACM Transactions on Interactive Intelligent Systems, Neurocomputing, Journal on Multimodal User Interfaces, Computational Statistics and Biologically Inspired Cognitive Architectures.

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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