Tobias Gindele

1.4k citations
16 papers · 977 indexed · h-index 15
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)
Partner nations
GermanySlovakia

In The Last Decade

Tobias Gindele

16 papers receiving 946 citations

Peers

Tobias Gindele
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
Replace Nico Kaempchen with:
Nico Kaempchen Germany
Sebastian Brechtel Germany
Georges S. Aoude United States
Michael Aeberhard Germany
Dizan Vasquez France
Tim A. Wheeler United States
Andreas Eidehall Sweden
Paul Vernaza United States
Robert Krajewski Germany
Hang Zhao China
Tobias Gindele relative to Nico Kaempchen Germany Nico Kaempchen's profile →
Citations per field
00.5×1.7×
Nico Kaempchen · 1×
Citations per year

Countries citing papers authored by Tobias Gindele

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

16 of 16 papers shown
#WorkIndexed 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.

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