Federico Paredes-Vallés
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Cognitive Neuroscience
- Aerospace Engineering
- Co-authors
- Guido de CroonJulien DupeyrouxChristophe De WagterSergio García-NietoJ.V. SalcedoLyes KhacefChristian VogtMarco Cannici
- Topics
- Advanced Memory and Neural Computing (6 papers)Neural dynamics and brain function (4 papers)Neural Networks and Reservoir Computing (4 papers)
- Cited by
- Computer Vision and Pattern RecognitionCognitive NeuroscienceElectrical and Electronic Engineering
- Partner nations
- NetherlandsTaiwanSwitzerland
In The Last Decade
Federico Paredes-Vallés
12 papers receiving 314 citations
Peers
Comparison fields: 5 of 48
- Electrical and Electronic Engineering 201
- Computer Vision and Pattern Recognition 106
- Artificial Intelligence 89
- Cognitive Neuroscience 83
- Aerospace Engineering 61
Countries citing papers authored by Federico Paredes-Vallés
This map shows the geographic impact of Federico Paredes-Vallés'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 Federico Paredes-Vallés with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Federico Paredes-Vallés more than expected).
Fields of papers citing papers by Federico Paredes-Vallés
This network shows the impact of papers produced by Federico Paredes-Vallés. 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 Federico Paredes-Vallés. The network helps show where Federico Paredes-Vallés may publish in the future.
Co-authorship network of co-authors of Federico Paredes-Vallés
This figure shows the co-authorship network connecting the top 25 collaborators of Federico Paredes-Vallés. A scholar is included among the top collaborators of Federico Paredes-Vallés 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 Federico Paredes-Vallés. Federico Paredes-Vallés 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 | 0 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 33 | |
| 6 | 13 | |
| 7 | 11 | |
| 8 | 14 | |
| 9 | 10 | |
| 10 | 7 | |
| 11 | 85 | |
| 12 | 19 | |
| 13 | 128 | |
| 14 | Neuromorphic Computing of Event-Based Data for High-Speed Vision-Based Navigation | 2 |
| 15 | Analysis of current and future web standards for reducing the gap between native and web applications | 0 |
About Federico Paredes-Vallés
Federico Paredes-Vallés is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Biophysics, having authored 15 papers that have together received 326 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (6 papers), Neural dynamics and brain function (4 papers) and Neural Networks and Reservoir Computing (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (106 citations), Cognitive Neuroscience (83 citations) and Electrical and Electronic Engineering (201 citations). Federico Paredes-Vallés has collaborated with scholars based in Netherlands, Taiwan and Switzerland. Frequent co-authors include Guido de Croon, Julien Dupeyroux, Christophe De Wagter, Sergio García-Nieto, J.V. Salcedo, Lyes Khacef, Christian Vogt, Marco Cannici, Michael Jost and Yahya Zweiri. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Science Robotics and Electronics.
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.