David F. Barrero

613 total citations
41 papers, 354 citations indexed

About

David F. Barrero is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, David F. Barrero has authored 41 papers receiving a total of 354 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 12 papers in Information Systems and 12 papers in Computer Vision and Pattern Recognition. Recurrent topics in David F. Barrero's work include Evolutionary Algorithms and Applications (6 papers), Metaheuristic Optimization Algorithms Research (6 papers) and User Authentication and Security Systems (5 papers). David F. Barrero is often cited by papers focused on Evolutionary Algorithms and Applications (6 papers), Metaheuristic Optimization Algorithms Research (6 papers) and User Authentication and Security Systems (5 papers). David F. Barrero collaborates with scholars based in Spain, United Kingdom and Netherlands. David F. Barrero's co-authors include María D. R‐Moreno, David Camacho, Héctor D. Menéndez, Pablo Muñoz, Gema Bello-Orgaz, Julio Hernández-Castro, Agustín Martínez, Pedro Peris‐Lopez, Adrian Stoica and Huosheng Hu and has published in prestigious journals such as Expert Systems with Applications, Sensors and Applied Sciences.

In The Last Decade

David F. Barrero

39 papers receiving 329 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David F. Barrero Spain 12 167 93 93 57 38 41 354
Yuxin Mao China 14 157 0.9× 111 1.2× 140 1.5× 181 3.2× 50 1.3× 66 554
Chiara Piacentini United Kingdom 8 270 1.6× 41 0.4× 132 1.4× 74 1.3× 37 1.0× 20 481
Xuyan Tu China 11 206 1.2× 51 0.5× 65 0.7× 85 1.5× 22 0.6× 107 439
Junli Li China 11 133 0.8× 78 0.8× 92 1.0× 88 1.5× 10 0.3× 32 404
Pethuru Raj India 12 76 0.5× 120 1.3× 145 1.6× 113 2.0× 47 1.2× 57 400
Margaret L. Loper United States 12 121 0.7× 42 0.5× 54 0.6× 143 2.5× 25 0.7× 46 428
Faisal Alkhateeb Jordan 12 241 1.4× 102 1.1× 73 0.8× 139 2.4× 60 1.6× 43 470
A. Şima Uyar Türkiye 12 257 1.5× 42 0.5× 50 0.5× 51 0.9× 24 0.6× 44 449
Mingsheng Fu China 10 246 1.5× 230 2.5× 143 1.5× 74 1.3× 31 0.8× 22 478
Haicheng Tao China 11 182 1.1× 98 1.1× 111 1.2× 60 1.1× 46 1.2× 27 428

Countries citing papers authored by David F. Barrero

Since Specialization
Citations

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

Fields of papers citing papers by David F. Barrero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David F. Barrero. 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 David F. Barrero. The network helps show where David F. Barrero may publish in the future.

Co-authorship network of co-authors of David F. Barrero

This figure shows the co-authorship network connecting the top 25 collaborators of David F. Barrero. A scholar is included among the top collaborators of David F. Barrero 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 David F. Barrero. David F. Barrero 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.
Barrero, David F., et al.. (2024). SWAN: A multihead autoregressive attention model for solar wind speed forecasting. Expert Systems with Applications. 252. 124128–124128. 8 indexed citations
2.
Barrero, David F., et al.. (2021). SOPRENE: Assessment of the Spanish Armada’s Predictive Maintenance Tool for Naval Assets. Applied Sciences. 11(16). 7322–7322. 6 indexed citations
3.
Muñoz, Pablo, et al.. (2021). Continuous energy consumption measure approach using a DMA double-buffering technique. EURASIP Journal on Wireless Communications and Networking. 2021(1). 1 indexed citations
4.
Muñoz, Pablo, et al.. (2020). A Simulator to Support Machine Learning-Based Wearable Fall Detection Systems. Electronics. 9(11). 1831–1831. 7 indexed citations
5.
Muñoz, Pablo, et al.. (2019). LARES: An AI-based teleassistance system for emergency home monitoring. Cognitive Systems Research. 56. 213–222. 12 indexed citations
6.
Muñoz, Pablo, et al.. (2018). MoBAr: a Hierarchical Action-Oriented Autonomous Control Architecture. Journal of Intelligent & Robotic Systems. 94(3-4). 745–760. 10 indexed citations
7.
Hernández-Castro, Julio & David F. Barrero. (2017). Evolutionary generation and degeneration of randomness to assess the indepedence of the Ent test battery. 1420–1427. 7 indexed citations
8.
Muñoz, Pablo, et al.. (2017). A Virtual Reality Mission Planner for Mars Rovers. 142–146. 3 indexed citations
9.
Barrero, David F., et al.. (2015). Machine learning and empathy: the Civil Rights CAPTCHA. Concurrency and Computation Practice and Experience. 28(4). 1310–1323. 2 indexed citations
10.
R‐Moreno, María D., et al.. (2015). Using JPEG to Measure Image Continuity and Break Capy and Other Puzzle CAPTCHAs. IEEE Internet Computing. 19(6). 46–53. 14 indexed citations
11.
Barrero, David F., et al.. (2014). A FRAMEWORK FOR MASSIVE TWITTER DATA EXTRACTION AND ANALYSIS. Malaysian Journal of Computer Science. 27(1). 50–67. 18 indexed citations
12.
Menéndez, Héctor D., David F. Barrero, & David Camacho. (2014). A GENETIC GRAPH-BASED APPROACH FOR PARTITIONAL CLUSTERING. International Journal of Neural Systems. 24(3). 1430008–1430008. 53 indexed citations
13.
R‐Moreno, María D., et al.. (2014). Efficient Services Management in Libraries using AI and Wireless techniques. Expert Systems with Applications. 41(17). 7904–7913. 13 indexed citations
14.
Muñoz, Pablo, David F. Barrero, & María D. R‐Moreno. (2014). A Statistically Rigorous Analysis of 2D Path-Planning Algorithms. The Computer Journal. 58(11). 2876–2891. 7 indexed citations
15.
Bello-Orgaz, Gema, David F. Barrero, María D. R‐Moreno, & David Camacho. (2013). Acquisition of business intelligence from human experience in route planning. Enterprise Information Systems. 9(3). 303–323. 9 indexed citations
16.
Bello-Orgaz, Gema, María D. R‐Moreno, David Camacho, & David F. Barrero. (2012). Clustering avatars behaviours from virtual worlds interactions. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 1–1. 22 indexed citations
17.
Barrero, David F. & María D. R‐Moreno. (2010). INFORMATION INTEGRATION IN SEARCHY: AN ONTOLOGY AND WEB SERVICES BASED APPROACH. 7. 14–29. 5 indexed citations
18.
Barrero, David F., Antonio González-Pardo, David Camacho, & María D. R‐Moreno. (2010). Distributed parameter tuning for genetic algorithms. Computer Science and Information Systems. 7(3). 661–677. 1 indexed citations
19.
Criado, J. Ignacio, et al.. (2004). Construyendo la e-Administración local: Las tecnologías de la Información y la Comunicación e Internet en los Ayuntamientos de la Comunidad de Madrid. Dialnet (Universidad de la Rioja). 487(1). 277–281. 1 indexed citations
20.
Criado, J. Ignacio & David F. Barrero. (2002). 30 años de vidas paralelas: Internet y Unix. 60–64. 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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