Fernando Torres

3.5k total citations
161 papers, 2.3k citations indexed

About

Fernando Torres is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition and Media Technology. According to data from OpenAlex, Fernando Torres has authored 161 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Control and Systems Engineering, 60 papers in Computer Vision and Pattern Recognition and 47 papers in Media Technology. Recurrent topics in Fernando Torres's work include Robot Manipulation and Learning (43 papers), Advanced Vision and Imaging (35 papers) and Robotics and Sensor-Based Localization (33 papers). Fernando Torres is often cited by papers focused on Robot Manipulation and Learning (43 papers), Advanced Vision and Imaging (35 papers) and Robotics and Sensor-Based Localization (33 papers). Fernando Torres collaborates with scholars based in Spain, France and United States. Fernando Torres's co-authors include Francisco A. Candelas-Herías, Jorge Pomares, Santiago Timoteo Puente Méndez, Carlos A. Jara, Pablo Gil, Juan Antonio Corrales Ramón, Gabriel J. García, S. Dormido, Francisco Ortiz and Rafaél Aracil and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Computers & Education.

In The Last Decade

Fernando Torres

147 papers receiving 2.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Fernando Torres Spain 25 724 627 489 470 469 161 2.3k
Dikai Liu Australia 28 735 1.0× 219 0.3× 617 1.3× 599 1.3× 583 1.2× 228 2.9k
Ville Kyrki Finland 27 1.1k 1.5× 184 0.3× 1.0k 2.1× 315 0.7× 608 1.3× 168 2.7k
Fakhreddine Karray Canada 12 649 0.9× 118 0.2× 407 0.8× 218 0.5× 221 0.5× 44 2.4k
C.S.G. Lee United States 20 1.1k 1.5× 166 0.3× 637 1.3× 297 0.6× 229 0.5× 67 2.9k
Jürgen Beyerer Germany 27 254 0.4× 235 0.4× 1.9k 3.8× 367 0.8× 276 0.6× 420 3.5k
Gang Chen China 23 716 1.0× 72 0.1× 639 1.3× 513 1.1× 298 0.6× 340 2.4k
R. Marı́n Spain 17 334 0.5× 132 0.2× 341 0.7× 409 0.9× 164 0.3× 113 1.2k
Cipriano Galindo Spain 20 420 0.6× 79 0.1× 718 1.5× 211 0.4× 129 0.3× 70 1.7k
Yang Xing Singapore 39 1.4k 2.0× 75 0.1× 1.1k 2.2× 249 0.5× 218 0.5× 116 5.1k
Humberto Sossa Mexico 24 220 0.3× 159 0.3× 795 1.6× 112 0.2× 133 0.3× 190 2.0k

Countries citing papers authored by Fernando Torres

Since Specialization
Citations

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

Fields of papers citing papers by Fernando Torres

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fernando Torres

This figure shows the co-authorship network connecting the top 25 collaborators of Fernando Torres. A scholar is included among the top collaborators of Fernando Torres 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 Torres. Fernando Torres 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
1.
Candelas-Herías, Francisco A., et al.. (2025). DualQuat-LOAM: LiDAR odometry and mapping parameterized on dual quaternions. Robotics and Autonomous Systems. 191. 105009–105009. 1 indexed citations
2.
Álvarez, Hugo, et al.. (2025). Deep learning-based solder joint defect detector. The International Journal of Advanced Manufacturing Technology. 137(9-10). 5133–5147.
3.
Candelas-Herías, Francisco A., et al.. (2024). ViKi-HyCo: A Hybrid-Control Approach for Complex Car-Like Maneuvers. IEEE Access. 12. 65428–65443.
4.
Candelas-Herías, Francisco A., et al.. (2024). Geo-Localization Based on Dynamically Weighted Factor-Graph. IEEE Robotics and Automation Letters. 9(6). 5599–5606. 3 indexed citations
5.
Stiller, Christoph, et al.. (2022). Robust Self-Tuning Data Association for Geo-Referencing Using Lane Markings. IEEE Robotics and Automation Letters. 7(4). 12339–12346. 4 indexed citations
6.
Candelas-Herías, Francisco A., et al.. (2022). OpenStreetMap-Based Autonomous Navigation With LiDAR Naive-Valley-Path Obstacle Avoidance. IEEE Transactions on Intelligent Transportation Systems. 23(12). 24428–24438. 16 indexed citations
7.
Úbeda, Andrés, Fernando Torres, & Santiago Timoteo Puente Méndez. (2020). Assistance Robotics and Biosensors 2019. Sensors. 20(5). 1335–1335. 2 indexed citations
8.
Méndez, Santiago Timoteo Puente, et al.. (2019). Virtualization of Robotic Hands Using Mobile Devices †. Robotics. 8(3). 81–81. 1 indexed citations
9.
Úbeda, Andrés, et al.. (2018). A Vision-Driven Collaborative Robotic Grasping System Tele-Operated by Surface Electromyography. Sensors. 18(7). 2366–2366. 6 indexed citations
10.
Gil, Pablo, et al.. (2016). Visual/Tactile sensing to monitor grasps with robot-hand for planar elastic objects. Repositorio Institucional de la Universidad de Alicante (Universidad de Alicante). 1–7. 2 indexed citations
11.
Sempere, Ángel Pérez, et al.. (2015). Control and Guidance of Low-Cost Robots via Gesture Perception for Monitoring Activities in the Home. Sensors. 15(12). 31268–31292. 7 indexed citations
13.
Gil, Pablo, Francisco A. Candelas-Herías, Carlos A. Jara, Gabriel J. García, & Fernando Torres. (2013). Web-based OERs in Computer Networks. International journal of engineering education. 29(6). 1537–1550. 15 indexed citations
14.
Pomares, Jorge, et al.. (2011). A Multi-Sensorial Hybrid Control for Robotic Manipulation in Human-Robot Workspaces. Sensors. 11(10). 9839–9862. 7 indexed citations
15.
Reinoso, Óscar, et al.. (2011). A web-based platform for remote interaction with mobile robots in higher education. International journal of engineering education. 27(2). 266–283. 4 indexed citations
16.
Gil, Pablo, Jorge Pomares, & Fernando Torres. (2010). Analysis and Adaptation of Integration Time in PMD Camera for Visual Servoing. RUA, Repositorio Institucional de la Universidad de Alicante (Universidad de Alicante). 311–315. 13 indexed citations
17.
Pomares, Jorge, Gabriel J. García, & Fernando Torres. (2006). Improving tracking trajectories with motion estimation. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 97–103. 3 indexed citations
18.
Candelas-Herías, Francisco A., Fernando Torres, Pablo Gil, et al.. (2004). Laboratorio virtual remoto para robótica y evaluación de su impacto en la docencia. Revista Iberoamericana de Automática e Informática Industrial RIAI. 1(2). 49–57. 14 indexed citations
19.
Pomares, Jorge, Pablo Gil, Santiago Timoteo Puente Méndez, & Fernando Torres. (2004). Learning environment for teaching robotics and sensorial system: application to the robots guidance. RUA, Repositorio Institucional de la Universidad de Alicante (Universidad de Alicante). 15. 301–306. 1 indexed citations
20.
Vicente, María Asunción, Pablo Gil, Óscar Reinoso, & Fernando Torres. (2002). Objects recognition by means of projective invariants considering corner-points. Digital Library (University of West Bohemia). 129–136. 1 indexed citations

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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