Tobias Gindele
- Automotive Engineering top 1%
- Control and Systems Engineering top 5%
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Building and Construction top 5%
- Co-authors
- Rüdiger DillmannSebastian BrechtelJoachim SchröderMoritz WerlingBenjamin PitzerChristoph StillerMatthias GoeblFelix von Hundelshausen
- Topics
- Autonomous Vehicle Technology and Safety (10 papers)Target Tracking and Data Fusion in Sensor Networks (5 papers)Bayesian Modeling and Causal Inference (4 papers)
- Cited by
- Automotive EngineeringComputer Vision and Pattern RecognitionSafety, Risk, Reliability and Quality
- Journals
- Journal of Field RoboticsIEEE Intelligent Transportation Systems MagazineDIAL (Catholic University of Leuven)
In The Last Decade
Tobias Gindele
16 papers receiving 946 citations
Peers
Comparison fields: 5 of 55
- Automotive Engineering 713
- Control and Systems Engineering 338
- Computer Vision and Pattern Recognition 337
- Artificial Intelligence 233
- Building and Construction 150
Countries citing papers authored by Tobias Gindele
This map shows the geographic impact of Tobias Gindele'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 Tobias Gindele with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tobias Gindele more than expected).
Fields of papers citing papers by Tobias Gindele
This network shows the impact of papers produced by Tobias Gindele. 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 Tobias Gindele. The network helps show where Tobias Gindele may publish in the future.
Co-authorship network of co-authors of Tobias Gindele
This figure shows the co-authorship network connecting the top 25 collaborators of Tobias Gindele. A scholar is included among the top collaborators of Tobias Gindele 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 Tobias Gindele. Tobias Gindele is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 22 | |
| 2 | 140 | |
| 3 | 198 | |
| 4 | Solving Continuous POMDPs: Value Iteration with Incremental Learning of an Efficient Space Representation | 24 |
| 5 | 44 | |
| 6 | 45 | |
| 7 | 152 | |
| 8 | 19 | |
| 9 | 56 | |
| 10 | 15 | |
| 11 | 16 | |
| 12 | 17 | |
| 13 | 11 | |
| 14 | 182 | |
| 15 | 20 | |
| 16 | 16 |
About Tobias Gindele
Tobias Gindele is a scholar working on Automotive Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 16 papers that have together received 977 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (10 papers), Target Tracking and Data Fusion in Sensor Networks (5 papers) and Bayesian Modeling and Causal Inference (4 papers). The work is most often cited by research in Automotive Engineering (713 citations), Computer Vision and Pattern Recognition (337 citations) and Safety, Risk, Reliability and Quality (148 citations). Tobias Gindele has collaborated with scholars based in Germany and Slovakia. Frequent co-authors include Rüdiger Dillmann, Sebastian Brechtel, Joachim Schröder, Moritz Werling, Benjamin Pitzer, Christoph Stiller, Matthias Goebl, Felix von Hundelshausen, Sören Kammel and Oliver Pink. Their work appears in journals such as Journal of Field Robotics, IEEE Intelligent Transportation Systems Magazine and DIAL (Catholic University of Leuven).
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.