A. Navia-Vázquez
- Signal Processing top 2%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Computational Mechanics top 5%
- Control and Systems Engineering top 10%
- Co-authors
- Anı́bal R. Figueiras-VidalJerónimo Arenas‐GarcíaAntonio Artés-Rodrı́guezFernando Pérez‐CruzManel Martínez‐RamónCarlos Guerrero-MosqueraEmilio Parrado-HernándezArmando Malanda
- Topics
- Blind Source Separation Techniques (14 papers)Neural Networks and Applications (14 papers)Face and Expression Recognition (13 papers)
- Journals
- IEEE Transactions on Signal ProcessingPattern RecognitionIEEE Transactions on Antennas and Propagation
- Partner nations
- SpainUnited StatesGreece
In The Last Decade
A. Navia-Vázquez
37 papers receiving 732 citations
Peers
Comparison fields: 5 of 94
- Signal Processing 315
- Artificial Intelligence 313
- Computer Vision and Pattern Recognition 197
- Computational Mechanics 191
- Control and Systems Engineering 107
Countries citing papers authored by A. Navia-Vázquez
This map shows the geographic impact of A. Navia-Vázquez'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 A. Navia-Vázquez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. Navia-Vázquez more than expected).
Fields of papers citing papers by A. Navia-Vázquez
This network shows the impact of papers produced by A. Navia-Vázquez. 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 A. Navia-Vázquez. The network helps show where A. Navia-Vázquez may publish in the future.
Co-authorship network of co-authors of A. Navia-Vázquez
This figure shows the co-authorship network connecting the top 25 collaborators of A. Navia-Vázquez. A scholar is included among the top collaborators of A. Navia-Vázquez 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 A. Navia-Vázquez. A. Navia-Vázquez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 8 | |
| 4 | Optimization of AMS using weighted AUC optimized models | 0 |
| 5 | 47 | |
| 6 | 63 | |
| 7 | 1 | |
| 8 | 3 | |
| 9 | 1 | |
| 10 | 27 | |
| 11 | 78 | |
| 12 | 39 | |
| 13 | 6 | |
| 14 | 9 | |
| 15 | 5 | |
| 16 | 4 | |
| 17 | 56 | |
| 18 | 29 | |
| 19 | Agents in decentralised information ecosystems:the diet approach | 13 |
| 20 | Fast Training of Support Vector Classifiers | 34 |
About A. Navia-Vázquez
A. Navia-Vázquez is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 39 papers that have together received 774 indexed citations. Recurring topics across this work include Blind Source Separation Techniques (14 papers), Neural Networks and Applications (14 papers) and Face and Expression Recognition (13 papers). The work is most often cited by research in Signal Processing (315 citations), Artificial Intelligence (313 citations) and Computer Vision and Pattern Recognition (197 citations). A. Navia-Vázquez has collaborated with scholars based in Spain, United States and Greece. Frequent co-authors include Anı́bal R. Figueiras-Vidal, Jerónimo Arenas‐García, Antonio Artés-Rodrı́guez, Fernando Pérez‐Cruz, Manel Martínez‐Ramón, Carlos Guerrero-Mosquera, Emilio Parrado-Hernández, Armando Malanda, F.J. González-Serrano and Inmaculada Mora-Jiménez. Their work appears in journals such as IEEE Transactions on Signal Processing, Pattern Recognition and IEEE Transactions on Antennas and Propagation.
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.