Oliver Wasenmüller
- Computer Vision and Pattern Recognition top 5%
- Aerospace Engineering top 10%
- Geology top 10%
- Computational Mechanics
- Artificial Intelligence
- Co-authors
- Didier StrickerMarcel MeyerJason RambachVladislav GolyanikJan PetersGabriele BleserMichael SchulzeGeorg Kuschk
- Topics
- Advanced Vision and Imaging (9 papers)Advanced Neural Network Applications (8 papers)Robotics and Sensor-Based Localization (7 papers)
In The Last Decade
Oliver Wasenmüller
25 papers receiving 271 citations
Peers
Comparison fields: 5 of 46
- Computer Vision and Pattern Recognition 189
- Aerospace Engineering 122
- Geology 53
- Computational Mechanics 29
- Artificial Intelligence 26
Countries citing papers authored by Oliver Wasenmüller
This map shows the geographic impact of Oliver Wasenmüller'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 Oliver Wasenmüller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Oliver Wasenmüller more than expected).
Fields of papers citing papers by Oliver Wasenmüller
This network shows the impact of papers produced by Oliver Wasenmüller. 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 Oliver Wasenmüller. The network helps show where Oliver Wasenmüller may publish in the future.
Co-authorship network of co-authors of Oliver Wasenmüller
This figure shows the co-authorship network connecting the top 25 collaborators of Oliver Wasenmüller. A scholar is included among the top collaborators of Oliver Wasenmüller 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 Oliver Wasenmüller. Oliver Wasenmüller 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 | 1 | |
| 3 | 0 | |
| 4 | 9 | |
| 5 | 3 | |
| 6 | 4 | |
| 7 | 15 | |
| 8 | 1 | |
| 9 | 3 | |
| 10 | 6 | |
| 11 | 7 | |
| 12 | 24 | |
| 13 | 36 | |
| 14 | 11 | |
| 15 | 6 | |
| 16 | 7 | |
| 17 | 24 | |
| 18 | 6 | |
| 19 | Joint Bilateral Mesh Denoising using Color Information and Local Anti-Shrinking | 1 |
| 20 | Correspondence chaining for enhanced dense 3D reconstruction | 0 |
About Oliver Wasenmüller
Oliver Wasenmüller is a scholar working on Computer Vision and Pattern Recognition, Instrumentation and Computer Graphics and Computer-Aided Design, having authored 29 papers that have together received 280 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (9 papers), Advanced Neural Network Applications (8 papers) and Robotics and Sensor-Based Localization (7 papers). The work is most often cited by research in Geology (53 citations), Computer Vision and Pattern Recognition (189 citations) and Instrumentation (19 citations). Oliver Wasenmüller has collaborated with scholars based in Germany, India and Iran. Frequent co-authors include Didier Stricker, Marcel Meyer, Jason Rambach, Vladislav Golyanik, Jan Peters, Gabriele Bleser, Michael Schulze, Georg Kuschk and Jamshid Shanbehzadeh. Their work appears in journals such as Sensors, International Journal of Computer Vision and Applied Sciences.
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.