Fernando Gómez-Bravo

35 papers receiving 567 citations

Peers

Fernando Gómez-Bravo
Comparison fields: 5 of 80
  • Computer Vision and Pattern Recognition 266
  • Control and Systems Engineering 260
  • Computer Networks and Communications 97
  • Electrical and Electronic Engineering 97
  • Automotive Engineering 94
Replace Gustavo Velasco-Hernandez with:
Gustavo Velasco-Hernandez Ireland
Dongsoo Har South Korea
Armando Sousa Portugal
Ting Zhu United States
De Jong Yeong Ireland
Donghui Li China
Khalil M. Ahmad Yousef Jordan
Roland Philippsen Switzerland
Malika Meghjani Singapore
Ugo Rosolia United States
Fernando Gómez-Bravo relative to Gustavo Velasco-Hernandez Ireland Gustavo Velasco-Hernandez's profile →
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Countries citing papers authored by Fernando Gómez-Bravo

Since Specialization
Citations

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

Fields of papers citing papers by Fernando Gómez-Bravo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fernando Gómez-Bravo. 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 Gómez-Bravo. The network helps show where Fernando Gómez-Bravo may publish in the future.

Co-authorship network of co-authors of Fernando Gómez-Bravo

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 3
3 0
4 6
5 33
6 93
7 48
8 14
9 11
10 78
11 2
12 1
13 14
14 69
15
Planificación de Trayectorias con el Algoritmo RRT. Aplicación a Robots No Holónomos
5
16 6
17 4
18
Autonomous parking and navigation by using soft-computing techniques
1
19 6
20 60

About Fernando Gómez-Bravo

Fernando Gómez-Bravo is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering and Hardware and Architecture, having authored 36 papers that have together received 599 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (17 papers), Control and Dynamics of Mobile Robots (10 papers) and Robotics and Sensor-Based Localization (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (266 citations), Control and Systems Engineering (260 citations) and Automotive Engineering (94 citations). Fernando Gómez-Bravo has collaborated with scholars based in Spain, Italy and Portugal. Frequent co-authors include Federico Cuesta, Anı́bal Ollero, Giuseppe Carbone, J. Galán, Antidio Viguria, Eduardo Castillo-Castañeda, Juan Carlos Fortes, Isabel Ribeiro, Alberto Vale and Inmaculada Pulido‐Calvo. Their work appears in journals such as The Science of The Total Environment, IEEE Transactions on Industrial Electronics and Expert Systems with Applications.

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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