Leonard Bauersfeld

1.3k citations
18 papers · 648 indexed · 1 hit paper · h-index 10
Topics
Robotics and Sensor-Based Localization (8 papers)Robotic Path Planning Algorithms (8 papers)Advanced Vision and Imaging (3 papers)
Journals
NatureSHILAP Revista de lepidopterologíaPLoS ONE

In The Last Decade

Leonard Bauersfeld

18 papers receiving 627 citations

Hit Papers

Champion-level drone racing using deep reinforcement lear...2023202620242025202350100150200250

Peers

Leonard Bauersfeld
Comparison fields: 5 of 67
  • Aerospace Engineering 259
  • Computer Vision and Pattern Recognition 233
  • Control and Systems Engineering 208
  • Artificial Intelligence 135
  • Automotive Engineering 76
Replace Yunlong Song with:
Yunlong Song Switzerland
Yifeng Niu China
Ángel Romero Switzerland
Mario Valenti United States
Shupeng Lai Singapore
Mark Cutler United States
Anthony Mallet France
Alessandro Renzaglia France
Isaac Miller United States
Joshua Redding United States
Leonard Bauersfeld relative to Yunlong Song Switzerland Yunlong Song's profile →
Citations per field
00.5×1.7×
Yunlong Song · 1×
Citations per year

Countries citing papers authored by Leonard Bauersfeld

Since Specialization
Citations

This map shows the geographic impact of Leonard Bauersfeld'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 Leonard Bauersfeld with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leonard Bauersfeld more than expected).

Fields of papers citing papers by Leonard Bauersfeld

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Leonard Bauersfeld. 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 Leonard Bauersfeld. The network helps show where Leonard Bauersfeld may publish in the future.

Co-authorship network of co-authors of Leonard Bauersfeld

This figure shows the co-authorship network connecting the top 25 collaborators of Leonard Bauersfeld. A scholar is included among the top collaborators of Leonard Bauersfeld 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 Leonard Bauersfeld. Leonard Bauersfeld is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
#WorkIndexed citations
1 7
2 37
3 2
4 8
5 11
6 2
7 11
8 12
9
Champion-level drone racing using deep reinforcement learningbreakdown →
286
10 6
11 4
12 13
13 48
14 71
15 39
16 86
17 1
18 4

About Leonard Bauersfeld

Leonard Bauersfeld is a scholar working on Acoustics and Ultrasonics, Computer Vision and Pattern Recognition and Aerospace Engineering, having authored 18 papers that have together received 648 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (8 papers), Robotic Path Planning Algorithms (8 papers) and Advanced Vision and Imaging (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (233 citations), Aerospace Engineering (259 citations) and Control and Systems Engineering (208 citations). Leonard Bauersfeld has collaborated with scholars based in Switzerland, United States and France. Frequent co-authors include Davide Scaramuzza, Elia Kaufmann, Antonio Loquercio, Matthias Müller, Vladlen Koltun, Guillaume Ducard, Christopher H. Onder, Ángel Romero, Giovanni Cioffi and Yunlong Song. Their work appears in journals such as Nature, SHILAP Revista de lepidopterología and PLoS ONE.

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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