Pedro E. López-de-Teruel

552 total citations
33 papers, 358 citations indexed

About

Pedro E. López-de-Teruel is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Aerospace Engineering. According to data from OpenAlex, Pedro E. López-de-Teruel has authored 33 papers receiving a total of 358 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Vision and Pattern Recognition, 12 papers in Electrical and Electronic Engineering and 8 papers in Aerospace Engineering. Recurrent topics in Pedro E. López-de-Teruel's work include Indoor and Outdoor Localization Technologies (10 papers), Advanced Image and Video Retrieval Techniques (9 papers) and Robotics and Sensor-Based Localization (8 papers). Pedro E. López-de-Teruel is often cited by papers focused on Indoor and Outdoor Localization Technologies (10 papers), Advanced Image and Video Retrieval Techniques (9 papers) and Robotics and Sensor-Based Localization (8 papers). Pedro E. López-de-Teruel collaborates with scholars based in Spain and Germany. Pedro E. López-de-Teruel's co-authors include A. Ruiz-Jimeno, Óscar Cánovas, Félix J. García Clemente, Ginés Garcı́a-Mateos, José M. Garcı́a, Manuel E. Acacio, Gregorio Bernabé, Ángel Luis Perales Gómez, M. Carmen Garrido and Rubèn González and has published in prestigious journals such as Sensors, Pattern Recognition and Applied Soft Computing.

In The Last Decade

Pedro E. López-de-Teruel

33 papers receiving 342 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Pedro E. López-de-Teruel Spain	10	171	91	80	71	51	33	358
Ali Amiri Iran	11	164 1.0×	100 1.1×	139 1.7×	62 0.9×	49 1.0×	30	429
Alaa E. Abdel-Hakim Egypt	11	451 2.6×	80 0.9×	71 0.9×	188 2.6×	73 1.4×	40	592
Kwang-Seok Moon South Korea	10	175 1.0×	40 0.4×	72 0.9×	50 0.7×	15 0.3×	46	298
Chengpo Mu China	9	118 0.7×	30 0.3×	57 0.7×	72 1.0×	49 1.0×	22	299
Rohin Daruwala India	9	113 0.7×	130 1.4×	36 0.5×	31 0.4×	33 0.6×	60	385
Mingyuan Xin China	10	70 0.4×	65 0.7×	73 0.9×	32 0.5×	21 0.4×	27	438
Haichuan Yang Japan	14	117 0.7×	83 0.9×	358 4.5×	70 1.0×	21 0.4×	74	604
A. Mittal India	10	570 3.3×	51 0.6×	97 1.2×	59 0.8×	45 0.9×	27	692

Countries citing papers authored by Pedro E. López-de-Teruel

Since Specialization

Citations

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

Fields of papers citing papers by Pedro E. López-de-Teruel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pedro E. López-de-Teruel. 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 Pedro E. López-de-Teruel. The network helps show where Pedro E. López-de-Teruel may publish in the future.

Co-authorship network of co-authors of Pedro E. López-de-Teruel

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

All Works

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20 of 20 papers shown

Gómez, Ángel Luis Perales, et al.. (2025). Fog computing-driven logistics: leveraging few-shot learning and foundational computer vision models. Cluster Computing. 28(14). 1 indexed citations

López-de-Teruel, Pedro E., et al.. (2025). Computer Vision on the Edge: A Scalable Auto-ID Solution for Industrial Logistics. Procedia Computer Science. 265. 276–284. 1 indexed citations

López-de-Teruel, Pedro E., et al.. (2024). A few-shot learning methodology for improving safety in industrial scenarios through universal self-supervised visual features and dense optical flow. Applied Soft Computing. 167. 112375–112375. 3 indexed citations

López-de-Teruel, Pedro E., et al.. (2023). Computer Vision Based Auto-ID for Optimizing Logistics Operations. 1–6. 3 indexed citations

Gómez, Ángel Luis Perales, et al.. (2022). FARMIT: continuous assessment of crop quality using machine learning and deep learning techniques for IoT-based smart farming. Cluster Computing. 25(3). 2163–2178. 27 indexed citations

López-de-Teruel, Pedro E., et al.. (2020). Negative results for approximation using single layer and multilayer feedforward neural networks. Journal of Mathematical Analysis and Applications. 494(1). 124584–124584. 7 indexed citations

Ruiz-Jimeno, A., et al.. (2017). Efficient planar affine canonicalization. Pattern Recognition. 72. 236–253. 2 indexed citations

López-de-Teruel, Pedro E., Félix J. García Clemente, & Óscar Cánovas. (2017). Practical passive localization system based on wireless signals for fast deployment of occupancy services. Future Generation Computer Systems. 107. 692–704. 7 indexed citations

Cánovas, Óscar, Pedro E. López-de-Teruel, & A. Ruiz-Jimeno. (2014). WiFiBoost: a terminal-based method for detection of indoor/outdoor places. 10 indexed citations

10.

Cánovas, Óscar, et al.. (2013). A vision-enhanced multisensor LBS suitable for augmented reality applications. Journal of Location Based Services. 7(3). 145–164. 3 indexed citations

11.

Cánovas, Óscar, et al.. (2012). A Multisensor Architecture Providing Location-based Services for Smartphones. Mobile Networks and Applications. 18(3). 310–325. 4 indexed citations

12.

López-de-Teruel, Pedro E., et al.. (2011). GEA optimization for live structureless motion estimation. 715–718. 9 indexed citations

13.

López-de-Teruel, Pedro E., et al.. (2011). Reduced epipolar cost for accelerated incremental SfM. 3097–3104. 19 indexed citations

14.

López-de-Teruel, Pedro E., et al.. (2008). QVision, a Development Framework for Real-time Computer Vision and Image Processing Research.. IPCV. 408–414. 1 indexed citations

15.

Garcı́a-Mateos, Ginés, et al.. (2008). Estimating 3D facial pose in video with just three points. 1–8. 4 indexed citations

16.

Acacio, Manuel E., Óscar Cánovas, José M. Garcı́a, & Pedro E. López-de-Teruel. (2002). MPI–Delphi: an MPI implementation for visual programming environments and heterogeneous computing. Future Generation Computer Systems. 18(3). 317–333. 2 indexed citations

17.

López-de-Teruel, Pedro E., et al.. (2002). A parallel algorithm for tracking of segments in noisy edge images. 4. 807–811. 2 indexed citations

18.

Acacio, Manuel E., José M. Garcı́a, & Pedro E. López-de-Teruel. (1999). A Performance Evaluation of P-EDR in Different Parallel Environments.. Parallel and Distributed Processing Techniques and Applications. 744–750. 1 indexed citations

19.

López-de-Teruel, Pedro E., José M. Garcı́a, & Manuel E. Acacio. (1999). The Parallel EM Algorithm and its Applications in Computer Vision.. Parallel and Distributed Processing Techniques and Applications. 571–578. 13 indexed citations

20.

Acacio, Manuel E., Pedro E. López-de-Teruel, José M. Garcı́a, & Óscar Cánovas. (1999). The MPI-Delphi Interface: A Visual Programming Environment for Clusters of Workstations.. Parallel and Distributed Processing Techniques and Applications. 183. 1730–1736. 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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