Georg Kuschk
- Instrumentation top 10%
-
- Advanced Vision and Imaging 11
- Advanced Neural Network Applications 2
- Aerospace Engineering top 10%
- Robotics and Sensor-Based Localization 6
- Advanced SAR Imaging Techniques 5
- Synthetic Aperture Radar (SAR) Applications and Techniques 2
- Geology top 10%
- 3D Surveying and Cultural Heritage 4
- Ocean Engineering top 10%
- Satellite Image Processing and Photogrammetry 5
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- Remote Sensing and LiDAR Applications 7
- Co-authors
- Michaël MeyerPablo d’AngeloSven TomfordeDaniel CremersPeter ReinartzDidier StrickerOliver WasenmüllerThomas Krauß
- Journals
- SHILAP Revista de lepidopterología (5 papers)IEEE Transactions on Geoscience and Remote Sensing (1 paper)International Journal of Computer Vision (1 paper)
- Partner nations
- Germany
In The Last Decade
Georg Kuschk
17 papers receiving 323 citations
Peers
Comparison fields: 5 of 36
- Instrumentation 36
- Computer Vision and Pattern Recognition 191
- Aerospace Engineering 172
- Geology 34
- Ocean Engineering 87
Countries citing papers authored by Georg Kuschk
This map shows the geographic impact of Georg Kuschk'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 Georg Kuschk with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Georg Kuschk more than expected).
Fields of papers citing papers by Georg Kuschk
This network shows the impact of papers produced by Georg Kuschk. 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 Georg Kuschk. The network helps show where Georg Kuschk may publish in the future.
Co-authorship network
The 12 scholars most cited alongside Georg Kuschk, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 1 | |
| 2 | 2021 | 44 | |
| 3 | 2020 | 9 | |
| 4 | Automotive Radar Dataset for Deep Learning Based 3D Object Detection | 2019 | 80 |
| 5 | Deep Learning Based 3D Object Detection for Automotive Radar and Camera | 2019 | 53 |
| 6 | 2019 | 11 | |
| 7 | 2017 | 3 | |
| 8 | 2016 | 10 | |
| 9 | 2015 | 5 | |
| 10 | 2015 | 1 | |
| 11 | 2014 | 23 | |
| 12 | 2014 | 3 | |
| 13 | 3D Reconstruction Chain - From Images to 3D City Model | 2013 | 1 |
| 14 | 2013 | 13 | |
| 15 | 2013 | 8 | |
| 16 | 2013 | 19 | |
| 17 | 2013 | 16 | |
| 18 | 2012 | 37 |
About Georg Kuschk
Georg Kuschk is a scholar working on Geology, Computer Vision and Pattern Recognition and Environmental Engineering, having authored 18 papers that have together received 337 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (11 papers), Remote Sensing and LiDAR Applications (7 papers), Robotics and Sensor-Based Localization (6 papers), Satellite Image Processing and Photogrammetry (5 papers), Advanced SAR Imaging Techniques (5 papers), 3D Surveying and Cultural Heritage (4 papers), Advanced Neural Network Applications (2 papers) and Synthetic Aperture Radar (SAR) Applications and Techniques (2 papers). The work is most often cited by research in Instrumentation (36 citations), Computer Vision and Pattern Recognition (191 citations) and Aerospace Engineering (172 citations). Georg Kuschk has collaborated with scholars based in Germany. Frequent co-authors include Michaël Meyer, Pablo d’Angelo, Sven Tomforde, Daniel Cremers, Peter Reinartz, Didier Stricker, Oliver Wasenmüller, Thomas Krauß, Jiaojiao Tian and Uwe Stilla. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Geoscience and Remote Sensing and International Journal of Computer Vision.
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.