David F. Barrero
- Artificial Intelligence top 10%
- Evolutionary Algorithms and Applications 6
- Metaheuristic Optimization Algorithms Research 6
- Semantic Web and Ontologies 5
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- Robotic Path Planning Algorithms 4
- Information Systems top 10%
- User Authentication and Security Systems 5
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- Advanced Malware Detection Techniques 5
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- Advanced Multi-Objective Optimization Algorithms 4
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- Advanced Database Systems and Queries 4
- Co-authors
- María D. R‐MorenoDavid CamachoHéctor D. MenéndezPablo MuñozGema Bello-OrgazJulio Hernández-CastroPedro Peris‐LopezAgustín Martínez
- Journals
- Expert Systems with Applications (3 papers)Robotics and Autonomous Systems (1 paper)Enterprise Information Systems (1 paper)
- Partner nations
- SpainUnited KingdomNetherlands
In The Last Decade
David F. Barrero
39 papers receiving 329 citations
Peers
Comparison fields: 5 of 74
- Artificial Intelligence 167
- Computer Vision and Pattern Recognition 93
- Information Systems 93
- Signal Processing 38
- Human-Computer Interaction 14
Countries citing papers authored by David F. Barrero
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
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
The 20 scholars most cited alongside David F. Barrero, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 6 | |
| 2 | 2021 | 1 | |
| 3 | 2020 | 7 | |
| 4 | 2019 | 12 | |
| 5 | 2018 | 10 | |
| 6 | 2017 | 7 | |
| 7 | 2017 | 3 | |
| 8 | 2015 | 2 | |
| 9 | A FRAMEWORK FOR MASSIVE TWITTER DATA EXTRACTION AND ANALYSIS | 2014 | 18 |
| 10 | 2014 | 13 | |
| 11 | 2014 | 53 | |
| 12 | 2014 | 7 | |
| 13 | 2014 | 10 | |
| 14 | 2013 | 9 | |
| 15 | 2012 | 22 | |
| 16 | 2012 | 16 | |
| 17 | INFORMATION INTEGRATION IN SEARCHY: AN ONTOLOGY AND WEB SERVICES BASED APPROACH | 2010 | 5 |
| 18 | 2010 | 1 | |
| 19 | 2004 | 1 | |
| 20 | 30 años de vidas paralelas: Internet y Unix | 2002 | 1 |
About David F. Barrero
David F. Barrero is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 41 papers that have together received 354 indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (6 papers), Metaheuristic Optimization Algorithms Research (6 papers), User Authentication and Security Systems (5 papers), Semantic Web and Ontologies (5 papers), Advanced Malware Detection Techniques (5 papers), Advanced Multi-Objective Optimization Algorithms (4 papers), Advanced Database Systems and Queries (4 papers) and Robotic Path Planning Algorithms (4 papers). The work is most often cited by research in Artificial Intelligence (167 citations), Computer Vision and Pattern Recognition (93 citations) and Information Systems (93 citations). David F. Barrero has collaborated with scholars based in Spain, United Kingdom and Netherlands. Frequent co-authors include María D. R‐Moreno, David Camacho, Héctor D. Menéndez, Pablo Muñoz, Gema Bello-Orgaz, Julio Hernández-Castro, Pedro Peris‐Lopez, Agustín Martínez, Adrian Stoica and Huosheng Hu. Their work appears in journals such as Expert Systems with Applications, Robotics and Autonomous Systems, Enterprise Information Systems, Genetic Programming and Evolvable Machines and IEEE Internet Computing.
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.