Lars Rosenbaum

2.5k citations
16 papers · 1.4k · 1 hit paper · h-index 12

Impact in

Papers in

Lars Rosenbaum

16 papers receiving 1.4k citations

Lars Rosenbaum's Hit Papers

Deep Multi-Modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges 2020 · 864 citations
8640+2+4Years since publication250500750

Peers

Lars Rosenbaum
Comparison fields: 5 of 150
  • Computer Vision and Pattern Recognition 610
  • Automotive Engineering 215
  • Instrumentation 41
  • Media Technology 82
  • Computational Theory and Mathematics 146
Replace Jianren Wang with:
Jianren Wang United States
Zhi Yan China
Xiaowei Shao China
Zhichao Lu China
Peng Chen China
Yilun Chen China
Yoshitaka Ushiku Japan
Yin Yang United States
Lars Rosenbaum relative to Jianren Wang United States Jianren Wang's profile →
Citations per field
00.5×10×15×19×
Jianren Wang · 1×
Citations per year

Countries citing papers authored by Lars Rosenbaum

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Lars Rosenbaum Line = papers co-authored together Lars Rosenbaum links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1
Deep Multi-Modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges
Hit paper breakdown →
2020864
2 2013216
3 201169
4 201950
5 201144
6 201434
7 201333
8 201127
9 202222
10 202117
11 202016
12 201513
13 20113
14 20123
15 20102
16 20111

About Lars Rosenbaum

Lars Rosenbaum is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 16 papers that have together received 1.4k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Machine Learning in Materials Science (6 papers), Metabolomics and Mass Spectrometry Studies (5 papers), Advanced Neural Network Applications (5 papers), Protein Structure and Dynamics (3 papers), Robotics and Sensor-Based Localization (2 papers), Autonomous Vehicle Technology and Safety (2 papers) and Cholinesterase and Neurodegenerative Diseases (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (610 citations), Automotive Engineering (215 citations), Instrumentation (41 citations), Media Technology (82 citations) and Computational Theory and Mathematics (146 citations). Lars Rosenbaum has collaborated with scholars based in Germany, United States and Sweden. Frequent co-authors include Di Feng, Klaus Dietmayer, Claudius Gläser, Fabian Timm, W. Wiesbeck, Christian Schütz, Heinz Hertlein, Andreas Zell, Georg Hinselmann and Andreas Jahn. Their work appears in journals such as Journal of Cheminformatics, IEEE Transactions on Intelligent Transportation Systems, Molecular Informatics, Clinical Chemistry and Journal of Chromatography B.

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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