Jan Faigl

133 papers receiving 2.0k citations

Peers

Jan Faigl
Comparison fields: 5 of 102
  • Computer Vision and Pattern Recognition 1.2k
  • Aerospace Engineering 969
  • Industrial and Manufacturing Engineering 314
  • Computer Networks and Communications 460
  • Computer Graphics and Computer-Aided Design 53
Replace Stefano Carpin with:
Stefano Carpin United States
P. B. Sujit India
Libor Přeučil Czechia
Iván Maza Spain
Nora Ayanian United States
Anthony Stentz United States
Ioan A. Şucan United States
Geoffrey A. Hollinger United States
A. Howard United States
Martin Saska Czechia
Jan Faigl relative to Stefano Carpin United States Stefano Carpin's profile →
Citations per field
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Stefano Carpin · 1×
Citations per year

Countries citing papers authored by Jan Faigl

Since Specialization
Citations

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

Fields of papers citing papers by Jan Faigl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jan Faigl, 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 Jan Faigl Line = papers co-authored together Jan Faigl links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 137 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014161
2 201698
3 200968
4 201766
5 201761
6 201361
7 201954
8 201053
9 201746
10 201244
11 201843
12 201243
13 202137
14 201136
15 201035
16 201333
17 201833
18 201932
19 201532
20 201931

About Jan Faigl

Jan Faigl is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Biomedical Engineering, Industrial and Manufacturing Engineering and Control and Systems Engineering, having authored 137 papers that have together received 2.1k indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (78 papers), Robotics and Sensor-Based Localization (44 papers), Robotic Locomotion and Control (29 papers), Vehicle Routing Optimization Methods (27 papers), Modular Robots and Swarm Intelligence (18 papers), Autonomous Vehicle Technology and Safety (11 papers), Metaheuristic Optimization Algorithms Research (10 papers) and Robot Manipulation and Learning (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.2k citations), Aerospace Engineering (969 citations), Industrial and Manufacturing Engineering (314 citations), Computer Networks and Communications (460 citations) and Computer Graphics and Computer-Aided Design (53 citations). Jan Faigl has collaborated with scholars based in Czechia, United Kingdom and United States. Frequent co-authors include Libor Přeučil, Petr Váňa, Martin Saska, Miroslav Kulich, Tomáš Krajník, Petr Čížek, Robert Pěnička, Geoffrey A. Hollinger, Graeme Best and Jan Chudoba. Their work appears in journals such as IEEE Robotics and Automation Letters, Autonomous Robots, Neurocomputing, Robotics and Autonomous Systems and Journal of Intelligent & Robotic Systems.

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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