Thomas Läbe
- Geology top 5%
- 3D Surveying and Cultural Heritage 4
- Environmental Engineering top 10%
- Remote Sensing and LiDAR Applications 6
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- Advanced Image and Video Retrieval Techniques 6
- Advanced Vision and Imaging 4
- Optical measurement and interference techniques 3
- Aerospace Engineering top 5%
- Robotics and Sensor-Based Localization 9
- Plant Science top 10%
- Smart Agriculture and AI 10
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- Satellite Image Processing and Photogrammetry 2
Thomas Läbe
20 papers receiving 501 citations
Peers
Comparison fields: 5 of 64
- Geology 111
- Environmental Engineering 150
- Computer Vision and Pattern Recognition 211
- Aerospace Engineering 227
- Plant Science 190
Countries citing papers authored by Thomas Läbe
This map shows the geographic impact of Thomas Läbe'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 Läbe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Läbe more than expected).
Fields of papers citing papers by Thomas Läbe
This network shows the impact of papers produced by Thomas Läbe. 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 Läbe. The network helps show where Thomas Läbe may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Thomas Läbe, 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 | 2025 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 0 | |
| 4 | 2023 | 2 | |
| 5 | 2023 | 19 | |
| 6 | 2023 | 13 | |
| 7 | 2023 | 14 | |
| 8 | 2022 | 34 | |
| 9 | 2022 | 16 | |
| 10 | 2021 | 32 | |
| 11 | 2021 | 90 | |
| 12 | 2020 | 28 | |
| 13 | 2019 | 38 | |
| 14 | 2018 | 61 | |
| 15 | 2017 | 36 | |
| 16 | 2016 | 23 | |
| 17 | 1 Trajectory Reconstruction Using Long Sequences of Digital Images From an Omnidirectional Camera | 2015 | 3 |
| 18 | 2013 | 19 | |
| 19 | GEOMETRIC STABILITY OF LOW-COST DIGITAL CONSUMER CAMERAS | 2012 | 25 |
| 20 | AUTOMATIC RELATIVE ORIENTATION OF IMAGES 1 | 2008 | 21 |
About Thomas Läbe
Thomas Läbe is a scholar working on Geology, Computer Vision and Pattern Recognition, Environmental Engineering, Aerospace Engineering and Plant Science, having authored 22 papers that have together received 518 indexed citations. Recurring topics across this work include Smart Agriculture and AI (10 papers), Robotics and Sensor-Based Localization (9 papers), Advanced Image and Video Retrieval Techniques (6 papers), Remote Sensing and LiDAR Applications (6 papers), Advanced Vision and Imaging (4 papers), 3D Surveying and Cultural Heritage (4 papers), Optical measurement and interference techniques (3 papers) and Satellite Image Processing and Photogrammetry (2 papers). The work is most often cited by research in Geology (111 citations), Environmental Engineering (150 citations), Computer Vision and Pattern Recognition (211 citations), Aerospace Engineering (227 citations) and Plant Science (190 citations). Thomas Läbe has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Cyrill Stachniss, Nived Chebrolu, Jens Behley, Federico Magistri, Andres Milioto, Xieyuanli Chen, Johannes Schneider, Philipp Lottes, Wolfgang Förstner and Chris McCool. Their work appears in journals such as IEEE Robotics and Automation Letters, Autonomous Robots, Sensors, PLoS ONE and Atmospheric chemistry and physics.
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.