Carlos Torre‐Ferrero

780 total citations · 1 hit paper
18 papers, 570 citations indexed

About

Carlos Torre‐Ferrero is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Control and Systems Engineering. According to data from OpenAlex, Carlos Torre‐Ferrero has authored 18 papers receiving a total of 570 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 5 papers in Aerospace Engineering and 4 papers in Control and Systems Engineering. Recurrent topics in Carlos Torre‐Ferrero's work include Robotics and Sensor-Based Localization (5 papers), 3D Surveying and Cultural Heritage (4 papers) and 3D Shape Modeling and Analysis (3 papers). Carlos Torre‐Ferrero is often cited by papers focused on Robotics and Sensor-Based Localization (5 papers), 3D Surveying and Cultural Heritage (4 papers) and 3D Shape Modeling and Analysis (3 papers). Carlos Torre‐Ferrero collaborates with scholars based in Spain, United Kingdom and Ecuador. Carlos Torre‐Ferrero's co-authors include J.R. Llata, Victor M. Becerra, Juan Pérez-Oria, Esther Gonzalez‐Sarabia, Teresa de Pedro, Vicente Milanés, Jorge Godoy, Ramón Sancibrián, Carlos Redondo‐Figuero and Ignacio Lombillo and has published in prestigious journals such as IEEE Access, Sensors and Electronics Letters.

In The Last Decade

Carlos Torre‐Ferrero

16 papers receiving 548 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Working Together: A Review on Safe Human-Robot Collaboration in Industrial Environments

2017 407 citations Victor M. Becerra, J.R. Llata et al. IEEE Access profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Carlos Torre‐Ferrero Spain	7	227	135	132	101	84	18	570
Juan Pérez-Oria Spain	7	246 1.1×	134 1.0×	111 0.8×	88 0.9×	74 0.9×	10	538
J.R. Llata Spain	8	232 1.0×	143 1.1×	116 0.9×	90 0.9×	76 0.9×	38	560
Nicola Maria Ceriani Italy	7	304 1.3×	93 0.7×	104 0.8×	113 1.1×	69 0.8×	8	441
Petr Novák Czechia	12	187 0.8×	94 0.7×	80 0.6×	131 1.3×	53 0.6×	32	587
Chiara Talignani Landi Italy	14	349 1.5×	84 0.6×	191 1.4×	87 0.9×	78 0.9×	16	547
Jun Kinugawa Japan	13	284 1.3×	76 0.6×	190 1.4×	134 1.3×	49 0.6×	48	503
Qi Zhu United States	13	152 0.7×	97 0.7×	60 0.5×	68 0.7×	101 1.2×	55	639
Jeremy A. Marvel United States	14	475 2.1×	308 2.3×	148 1.1×	189 1.9×	118 1.4×	68	841
Dong Zhou China	12	282 1.2×	112 0.8×	42 0.3×	102 1.0×	58 0.7×	52	807
Xiumin Fan China	16	105 0.5×	277 2.1×	98 0.7×	166 1.6×	124 1.5×	71	781

Countries citing papers authored by Carlos Torre‐Ferrero

Since Specialization

Citations

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

Fields of papers citing papers by Carlos Torre‐Ferrero

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Carlos Torre‐Ferrero. 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 Carlos Torre‐Ferrero. The network helps show where Carlos Torre‐Ferrero may publish in the future.

Co-authorship network of co-authors of Carlos Torre‐Ferrero

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

All Works

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18 of 18 papers shown

Llata, J.R., et al.. (2025). Guided Reinforcement Learning with Twin Delayed Deep Deterministic Policy Gradient for a Rotary Flexible-Link System. Robotics. 14(6). 76–76.

Llata, J.R., et al.. (2024). Optimization of Q and R Matrices with Genetic Algorithms to Reduce Oscillations in a Rotary Flexible Link System. Robotics. 13(6). 84–84. 1 indexed citations

Sancibrián, Ramón, Esther Gonzalez‐Sarabia, J. Blanco, Ignacio Lombillo, & Carlos Torre‐Ferrero. (2019). AVOIDING DESIGN FIXATION TO IMPROVE THE STUDENTS’ CREATIVE CAPABILITIES. INTED proceedings. 1. 6312–6317.

Sancibrián, Ramón, et al.. (2017). A METHOD FOR ASSESSING CREATIVITY AND INNOVATION OF INDUSTRIAL PRODUCTS BY ENGINEERING STUDENTS. EDULEARN proceedings. 1. 3038–3045. 1 indexed citations

Becerra, Victor M., et al.. (2017). Working Together: A Review on Safe Human-Robot Collaboration in Industrial Environments. IEEE Access. 5. 26754–26773. 407 indexed citations breakdown →

Sancibrián, Ramón, et al.. (2017). INDUSTRY OF THE FUTURE: IMPLEMENTATION OF COLLABORATIVE CAE TOOLS IN INDUSTRIAL ENGINEERING DEGREES. INTED proceedings. 1. 4676–4685. 1 indexed citations

Sancibrián, Ramón, et al.. (2014). Design and evaluation of a new ergonomic handle for instruments in minimally invasive surgery. Journal of Surgical Research. 188(1). 88–99. 35 indexed citations

Torre‐Ferrero, Carlos, et al.. (2014). Monovision‐based vehicle detection, distance and relative speed measurement in urban traffic. IET Intelligent Transport Systems. 8(8). 655–664. 28 indexed citations

Llata, J.R., et al.. (2014). Visual sensor fusion for active security in robotic industrial environments. EURASIP Journal on Advances in Signal Processing. 2014(1). 20 indexed citations

10.

Llata, J.R., et al.. (2013). Accurate Estimation of Airborne Ultrasonic Time-of-Flight for Overlapping Echoes. Sensors. 13(11). 15465–15488. 16 indexed citations

11.

Torre‐Ferrero, Carlos, et al.. (2012). 3D point cloud registration based on a purpose-designed similarity measure. EURASIP Journal on Advances in Signal Processing. 2012(1). 4 indexed citations

12.

Milanés, Vicente, et al.. (2011). Ultrasonic Sensors in Urban Traffic Driving-Aid Systems. Sensors. 11(1). 661–673. 39 indexed citations

13.

Torre‐Ferrero, Carlos, et al.. (2011). 3D registration of point clouds from time-of-flight cameras. Electronics Letters. 47(3). 175–177. 1 indexed citations

14.

Llata, J.R., et al.. (2010). An Approach for detecting and tracking oil slicks on satellite images. 71. 1–7. 4 indexed citations

15.

Torre‐Ferrero, Carlos, et al.. (2009). A similarity measure for 3D rigid registration of point clouds using image-based descriptors with low overlap. 2. 71–78. 8 indexed citations

16.

Torre‐Ferrero, Carlos, et al.. (2008). A coarse-to-fine algorithm for 3D registration based on wavelet decomposition. International Conference on Systems. 7(7). 655–664. 1 indexed citations

17.

Torre‐Ferrero, Carlos, et al.. (2007). 3D registration by using an alternative 3D shape representation. International Conference on Signal Processing. 101–106. 1 indexed citations

18.

Torre‐Ferrero, Carlos, et al.. (2006). CIRCON: An Alternative 3D Shape Representation for Surface Matching. Proceedings of the Annual Conference of the IEEE Industrial Electronics Society. 3320–3323. 3 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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