Thomas Martinetz

8.8k citations
131 papers · 5.5k indexed · 4 hit papers · h-index 31

Thomas Martinetz

125 papers receiving 5.1k citations

Hit Papers

Explainable...1571993202620042015250500750

Peers

Thomas Martinetz
Comparison fields: 5 of 195
  • Computer Vision and Pattern Recognition 1.7k
  • Cognitive Neuroscience 1.5k
  • Human-Computer Interaction 343
  • Artificial Intelligence 1.9k
  • Signal Processing 493
Replace T.M. McGinnity with:
T.M. McGinnity United Kingdom
David S. Touretzky United States
Shin Ishii Japan
Dimitris Metaxas United States
Fuhui Long United States
Linlin Shen China
Paul Sajda United States
Felix A. Wichmann Germany
Robert A. Jacobs United States
Tom Heskes Netherlands
Thomas Martinetz relative to T.M. McGinnity United Kingdom T.M. McGinnity's profile →
Citations per field
00.5×3.0×
T.M. McGinnity · 1×
Citations per year

Countries citing papers authored by Thomas Martinetz

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Martinetz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Thomas Martinetz, 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 Thomas Martinetz Line = papers co-authored together Thomas Martinetz links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20242
2 20240
3 20233
4 20231
5 20229
6 20228
7 20211
8 201510
9
Learning and modeling big data
20144
10
Auditory Closed-Loop Stimulation of the Sleep Slow Oscillation Enhances Memorybreakdown →
2013587
11 201251
12 201222
13 201120
14
Learning Data Representations with Sparse Coding Neural Gas
20088
15 200860
16
The Intrinsic Recurrent Support Vector Machine
20074
17
Predicting, analysing, and guiding eye movements
20050
18 20052
19
Saliency Extraction for Gaze-Contingent Displays
20041
20 19992

About Thomas Martinetz

Thomas Martinetz is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Health Informatics, having authored 131 papers that have together received 5.5k indexed citations. Recurring topics across this work include Neural Networks and Applications (19 papers), Gaze Tracking and Assistive Technology (17 papers), Visual Attention and Saliency Detection (12 papers), Blind Source Separation Techniques (11 papers), Neural dynamics and brain function (11 papers), Sleep and Wakefulness Research (11 papers), Machine Learning in Bioinformatics (10 papers) and Sparse and Compressive Sensing Techniques (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.7k citations), Cognitive Neuroscience (1.5k citations) and Human-Computer Interaction (343 citations). Thomas Martinetz has collaborated with scholars based in Germany, United States and Egypt. Frequent co-authors include Klaus Schulten, Erhardt Barth, Klaus Schulten, Matthias Mölle, Helge Ritter, Jan Born, Hong‐Viet V. Ngo, Michael Dörr, Hammam Alshazly and Christoph Linse. Their work appears in journals such as Neurocomputing, Journal of Theoretical Biology, PLoS ONE, IEEE Access and Sensors.

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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