Fernando Martín
- Computer Vision and Pattern Recognition top 5%
- Aerospace Engineering top 10%
- Control and Systems Engineering top 10%
- Biomedical Engineering
- Materials Chemistry
- Co-authors
- Luís MorenoSantiago GarridoMohamed AbderrahimDolores BlancoConcepción A. MonjeDorin CopaciCarlos BalaguerRudolph Triebel
- Topics
- Robotics and Sensor-Based Localization (18 papers)Robotic Path Planning Algorithms (11 papers)Advanced Vision and Imaging (6 papers)
- Cited by
- Computer Vision and Pattern RecognitionAerospace EngineeringControl and Systems Engineering
- Partner nations
- SpainAustraliaSwitzerland
In The Last Decade
Fernando Martín
29 papers receiving 433 citations
Peers
Comparison fields: 5 of 66
- Computer Vision and Pattern Recognition 226
- Aerospace Engineering 176
- Control and Systems Engineering 119
- Biomedical Engineering 109
- Materials Chemistry 46
Countries citing papers authored by Fernando Martín
This map shows the geographic impact of Fernando Martín'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 Fernando Martín with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fernando Martín more than expected).
Fields of papers citing papers by Fernando Martín
This network shows the impact of papers produced by Fernando Martín. 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 Fernando Martín. The network helps show where Fernando Martín may publish in the future.
Co-authorship network of co-authors of Fernando Martín
This figure shows the co-authorship network connecting the top 25 collaborators of Fernando Martín. A scholar is included among the top collaborators of Fernando Martín 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 Fernando Martín. Fernando Martín is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 40 | |
| 3 | 32 | |
| 4 | 15 | |
| 5 | 7 | |
| 6 | 5 | |
| 7 | 36 | |
| 8 | 1 | |
| 9 | 10 | |
| 10 | 2 | |
| 11 | 1 | |
| 12 | 16 | |
| 13 | 4 | |
| 14 | 1 | |
| 15 | 10 | |
| 16 | 4 | |
| 17 | 2 | |
| 18 | 3 | |
| 19 | 11 | |
| 20 | 144 |
About Fernando Martín
Fernando Martín is a scholar working on Aerospace Engineering, Computer Vision and Pattern Recognition and Control and Systems Engineering, having authored 29 papers that have together received 445 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (18 papers), Robotic Path Planning Algorithms (11 papers) and Advanced Vision and Imaging (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (226 citations), Aerospace Engineering (176 citations) and Control and Systems Engineering (119 citations). Fernando Martín has collaborated with scholars based in Spain, Australia and Switzerland. Frequent co-authors include Luís Moreno, Santiago Garrido, Mohamed Abderrahim, Dolores Blanco, Concepción A. Monje, Dorin Copaci, Carlos Balaguer, Rudolph Triebel, Roland Siegwart and Jaime Valls Miró. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Sensors.
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.