Lars Rosenbaum
Impact in
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- Advanced Neural Network Applications
- Video Surveillance and Tracking Methods
- Automotive Engineering top 5%
- Autonomous Vehicle Technology and Safety
Papers in
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- Computational Drug Discovery Methods 7
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- Metabolomics and Mass Spectrometry Studies 3
- Protein Structure and Dynamics 2
- Co-authors
- Di Feng (4 shared papers)Klaus Dietmayer (4 shared papers)Fabian Timm (3 shared papers)Claudius Gläser (2 shared papers)Heinz Hertlein (1 shared paper)W. Wiesbeck (1 shared paper)Christian Schütz (1 shared paper)Andreas Zell (11 shared papers)
- Journals
- Journal of Cheminformatics (5 papers)Molecular Informatics (2 papers)IEEE Transactions on Intelligent Transportation Systems (2 papers)Clinical Chemistry (1 paper)Journal of Chemical Information and Modeling (1 paper)
- Partner nations
- GermanyUnited StatesNetherlands
In The Last Decade
Lars Rosenbaum
16 papers receiving 1.4k citations
Lars Rosenbaum's Hit Papers
Peers
Comparison fields: 5 of 149
- Computer Vision and Pattern Recognition 623
- Automotive Engineering 221
- Instrumentation 41
- Media Technology 86
- Computational Theory and Mathematics 141
Countries citing papers authored by Lars Rosenbaum
This map shows the geographic impact of Lars Rosenbaum'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 Lars Rosenbaum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lars Rosenbaum more than expected).
Fields of papers citing papers by Lars Rosenbaum
This network shows the impact of papers produced by Lars Rosenbaum. 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 Lars Rosenbaum. The network helps show where Lars Rosenbaum may publish in the future.
Co-authors
The 25 scholars most cited alongside Lars Rosenbaum, 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 | Deep Multi-Modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges Hit paper breakdown → | 2020 | 898 |
| 2 | 2013 | 218 | |
| 3 | 2011 | 70 | |
| 4 | 2019 | 53 | |
| 5 | 2011 | 45 | |
| 6 | 2014 | 35 | |
| 7 | 2013 | 35 | |
| 8 | 2011 | 27 | |
| 9 | 2022 | 24 | |
| 10 | 2021 | 18 | |
| 11 | 2020 | 16 | |
| 12 | 2015 | 13 | |
| 13 | 2011 | 4 | |
| 14 | 2012 | 3 | |
| 15 | 2010 | 2 | |
| 16 | 2011 | 1 |
About Lars Rosenbaum
Lars Rosenbaum is a scholar working on Computational Theory and Mathematics, Molecular Biology, Computer Vision and Pattern Recognition, Artificial Intelligence and Materials Chemistry, having authored 16 papers that have together received 1.5k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Advanced Neural Network Applications (5 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Machine Learning in Materials Science (3 papers), Autonomous Vehicle Technology and Safety (2 papers), Protein Structure and Dynamics (2 papers), Robotics and Sensor-Based Localization (2 papers) and Diet and metabolism studies (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (623 citations), Automotive Engineering (221 citations), Instrumentation (41 citations), Media Technology (86 citations) and Computational Theory and Mathematics (141 citations). Lars Rosenbaum has collaborated with scholars based in Germany, United States and Netherlands. Frequent co-authors include Di Feng, Klaus Dietmayer, Fabian Timm, Claudius Gläser, Heinz Hertlein, W. Wiesbeck, Christian Schütz, Andreas Zell, Andreas Jahn and Georg Hinselmann. Their work appears in journals such as Journal of Cheminformatics, Molecular Informatics, IEEE Transactions on Intelligent Transportation Systems, Clinical Chemistry and Journal of Chemical Information and Modeling.
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.