Martin Kajan
- Computer Vision and Pattern Recognition top 2%
- Aerospace Engineering top 5%
- Control and Systems Engineering top 5%
- Computer Networks and Communications top 10%
- Automotive Engineering top 10%
- Co-authors
- František DuchoňPeter BeňoMartin FlorekAndrej BabinecTomáš FicoLadislav JurišicaPeter HubinskýMartin Dekan
- Topics
- Robotic Path Planning Algorithms (5 papers)Robotics and Sensor-Based Localization (2 papers)Advanced Surface Polishing Techniques (1 paper)
- Cited by
- Computer Vision and Pattern RecognitionAerospace EngineeringControl and Systems Engineering
- Journals
- IEEE Sensors JournalProcedia EngineeringAmerican journal of mechanical engineering
In The Last Decade
Martin Kajan
7 papers receiving 606 citations
Hit Papers
Peers
Comparison fields: 5 of 64
- Computer Vision and Pattern Recognition 485
- Aerospace Engineering 292
- Control and Systems Engineering 208
- Computer Networks and Communications 79
- Automotive Engineering 77
Countries citing papers authored by Martin Kajan
This map shows the geographic impact of Martin Kajan'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 Martin Kajan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Kajan more than expected).
Fields of papers citing papers by Martin Kajan
This network shows the impact of papers produced by Martin Kajan. 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 Martin Kajan. The network helps show where Martin Kajan may publish in the future.
Co-authorship network of co-authors of Martin Kajan
This figure shows the co-authorship network connecting the top 25 collaborators of Martin Kajan. A scholar is included among the top collaborators of Martin Kajan 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 Martin Kajan. Martin Kajan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 0 | |
| 3 | 10 | |
| 4 | 7 | |
| 5 | 6 | |
| 6 | Path Planning with Modified a Star Algorithm for a Mobile Robotbreakdown → | 594 |
| 7 | 5 | |
| 8 | 6 |
About Martin Kajan
Martin Kajan is a scholar working on Instrumentation, Computer Vision and Pattern Recognition and Control and Systems Engineering, having authored 8 papers that have together received 637 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (5 papers), Robotics and Sensor-Based Localization (2 papers) and Advanced Surface Polishing Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (485 citations), Aerospace Engineering (292 citations) and Control and Systems Engineering (208 citations). Martin Kajan has collaborated with scholars based in Slovakia and Zambia. Frequent co-authors include František Duchoň, Peter Beňo, Martin Florek, Andrej Babinec, Tomáš Fico, Ladislav Jurišica, Peter Hubinský, Martin Dekan, Mikuláš Huba and Michal Tölgyessy. Their work appears in journals such as IEEE Sensors Journal, Procedia Engineering and American journal of mechanical engineering.
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.