Markus Götz
Impact in
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- 3D Surveying and Cultural Heritage
Papers in
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- Neural Networks and Applications 4
- Co-authors
- Morris Riedel (9 shared papers)Charlotte Debus (16 shared papers)Achim Streit (15 shared papers)Gabriele Cavallaro (4 shared papers)Felix Laufer (3 shared papers)Ulrich W. Paetzold (3 shared papers)Hartwig Anzt (3 shared papers)Alexander Schug (4 shared papers)
- Journals
- Nature Machine Intelligence (2 papers)Journal of Visualized Experiments (1 paper)Advanced Materials (1 paper)Scientific Data (1 paper)IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (1 paper)
- Partner nations
- GermanyIcelandUnited States
In The Last Decade
Markus Götz
37 papers receiving 333 citations
Peers
Comparison fields: 5 of 79
- Computer Graphics and Computer-Aided Design 13
- Geology 18
- Media Technology 28
- Computer Vision and Pattern Recognition 65
- Artificial Intelligence 80
Countries citing papers authored by Markus Götz
This map shows the geographic impact of Markus Götz'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 Markus Götz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Götz more than expected).
Fields of papers citing papers by Markus Götz
This network shows the impact of papers produced by Markus Götz. 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 Markus Götz. The network helps show where Markus Götz may publish in the future.
Co-authors
The 25 scholars most cited alongside Markus Götz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 35 | |
| 2 | 2022 | 29 | |
| 3 | 2021 | 28 | |
| 4 | 2023 | 23 | |
| 5 | 2023 | 22 | |
| 6 | 2018 | 22 | |
| 7 | 2018 | 21 | |
| 8 | 2023 | 19 | |
| 9 | 2023 | 16 | |
| 10 | 2025 | 12 | |
| 11 | 2018 | 12 | |
| 12 | 2023 | 11 | |
| 13 | 2024 | 10 | |
| 14 | 2015 | 9 | |
| 15 | 2022 | 8 | |
| 16 | 2023 | 6 | |
| 17 | 2023 | 5 | |
| 18 | 2020 | 5 | |
| 19 | 2022 | 5 | |
| 20 | 2022 | 5 |
About Markus Götz
Markus Götz is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Materials Chemistry and Molecular Biology, having authored 45 papers that have together received 343 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (5 papers), 3D Surveying and Cultural Heritage (4 papers), Neural Networks and Applications (4 papers), Scientific Computing and Data Management (4 papers), Parallel Computing and Optimization Techniques (4 papers), Advanced Neural Network Applications (3 papers), Remote-Sensing Image Classification (3 papers) and Advanced Data Storage Technologies (3 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (13 citations), Geology (18 citations), Media Technology (28 citations), Computer Vision and Pattern Recognition (65 citations) and Artificial Intelligence (80 citations). Markus Götz has collaborated with scholars based in Germany, Iceland and United States. Frequent co-authors include Morris Riedel, Charlotte Debus, Achim Streit, Gabriele Cavallaro, Felix Laufer, Ulrich W. Paetzold, Hartwig Anzt, Alexander Schug, J. Kahn and Rebekka Volk. Their work appears in journals such as Nature Machine Intelligence, Journal of Visualized Experiments, Advanced Materials, Scientific Data and IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
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.