Martin Sundermeyer
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 2%
- Signal Processing top 2%
- Control and Systems Engineering top 5%
- Aerospace Engineering top 10%
- Co-authors
- Hermann NeyRalf SchlüterRudolph TriebelTamer AlkhouliJoern WuebkerMaximilian DurnerZoltán-Csaba MártonZoltán Tüske
- Topics
- Natural Language Processing Techniques (13 papers)Speech Recognition and Synthesis (12 papers)Topic Modeling (9 papers)
- Journals
- International Journal of Computer VisionIEEE/ACM Transactions on Audio Speech and Language Processing2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
In The Last Decade
Martin Sundermeyer
24 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 147
- Artificial Intelligence 1.3k
- Computer Vision and Pattern Recognition 533
- Signal Processing 343
- Control and Systems Engineering 207
- Aerospace Engineering 177
Countries citing papers authored by Martin Sundermeyer
This map shows the geographic impact of Martin Sundermeyer'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 Martin Sundermeyer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Sundermeyer more than expected).
Fields of papers citing papers by Martin Sundermeyer
This network shows the impact of papers produced by Martin Sundermeyer. 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 Martin Sundermeyer. The network helps show where Martin Sundermeyer may publish in the future.
Co-authorship network of co-authors of Martin Sundermeyer
This figure shows the co-authorship network connecting the top 25 collaborators of Martin Sundermeyer. A scholar is included among the top collaborators of Martin Sundermeyer 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 Martin Sundermeyer. Martin Sundermeyer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 5 | |
| 3 | 14 | |
| 4 | 55 | |
| 5 | 11 | |
| 6 | 31 | |
| 7 | Rock Instance Segmentation from Synthetic Images for Planetary Exploration Missions | 4 |
| 8 | BlenderProc: Reducing the Reality Gap with Photorealistic Rendering | 36 |
| 9 | 86 | |
| 10 | Improvements in language and translation modeling | 3 |
| 11 | From Feedforward to Recurrent LSTM Neural Networks for Language Modelingbreakdown → | 360 |
| 12 | 118 | |
| 13 | 28 | |
| 14 | 80 | |
| 15 | LSTM neural networks for language modelingbreakdown → | 1226 |
| 16 | 22 | |
| 17 | 21 | |
| 18 | 36 | |
| 19 | 20 | |
| 20 | 16 |
About Martin Sundermeyer
Martin Sundermeyer is a scholar working on Computer Vision and Pattern Recognition, Geology and Artificial Intelligence, having authored 26 papers that have together received 2.3k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (13 papers), Speech Recognition and Synthesis (12 papers) and Topic Modeling (9 papers). The work is most often cited by research in Artificial Intelligence (1.3k citations), Signal Processing (343 citations) and Computer Vision and Pattern Recognition (533 citations). Martin Sundermeyer has collaborated with scholars based in Germany, France and China. Frequent co-authors include Hermann Ney, Ralf Schlüter, Rudolph Triebel, Tamer Alkhouli, Joern Wuebker, Maximilian Durner, Zoltán-Csaba Márton, Zoltán Tüske, Ilya Oparin and J.-L. Gauvain. Their work appears in journals such as International Journal of Computer Vision, IEEE/ACM Transactions on Audio Speech and Language Processing and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.