Miguel A. Ferrer
- Computer Vision and Pattern Recognition top 0.5%
- Signal Processing top 0.5%
- Artificial Intelligence top 1%
- Media Technology top 0.5%
- Information Systems top 1%
- Co-authors
- Carlos M. TraviesoJesús B. AlonsoAythami MoralesMoises DíazJ. Francisco VargasPatricia HenríquezRéjean PlamondonUmapada Pal
- Topics
- Handwritten Text Recognition Techniques (74 papers)Biometric Identification and Security (60 papers)Face recognition and analysis (33 papers)
In The Last Decade
Miguel A. Ferrer
200 papers receiving 3.8k citations
Peers
Comparison fields: 5 of 166
- Computer Vision and Pattern Recognition 2.3k
- Signal Processing 1.2k
- Artificial Intelligence 936
- Media Technology 651
- Information Systems 505
Countries citing papers authored by Miguel A. Ferrer
This map shows the geographic impact of Miguel A. Ferrer'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 Miguel A. Ferrer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miguel A. Ferrer more than expected).
Fields of papers citing papers by Miguel A. Ferrer
This network shows the impact of papers produced by Miguel A. Ferrer. 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 Miguel A. Ferrer. The network helps show where Miguel A. Ferrer may publish in the future.
Co-authorship network of co-authors of Miguel A. Ferrer
This figure shows the co-authorship network connecting the top 25 collaborators of Miguel A. Ferrer. A scholar is included among the top collaborators of Miguel A. Ferrer 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 Miguel A. Ferrer. Miguel A. Ferrer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 4 | |
| 6 | 5 | |
| 7 | 6 | |
| 8 | 83 | |
| 9 | 6 | |
| 10 | 5 | |
| 11 | 7 | |
| 12 | 15 | |
| 13 | Design of a synchronous FFHSS modulator on a FPGA with system generator | 2 |
| 14 | 41 | |
| 15 | Evaluación acústica del sistema fonador | 0 |
| 16 | 84 | |
| 17 | Advances in automatic detection of failures in electric machines using audio signals | 1 |
| 18 | Writer identification by handwritten text analysis | 3 |
| 19 | Application of support vector machines and Gaussian Mixture Models for the detection of obstructive sleep apnoea based on the RR series | 11 |
| 20 | 21 |
About Miguel A. Ferrer
Miguel A. Ferrer is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Human-Computer Interaction, having authored 211 papers that have together received 4.1k indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (74 papers), Biometric Identification and Security (60 papers) and Face recognition and analysis (33 papers). The work is most often cited by research in Signal Processing (1.2k citations), Computer Vision and Pattern Recognition (2.3k citations) and Media Technology (651 citations). Miguel A. Ferrer has collaborated with scholars based in Spain, India and Italy. Frequent co-authors include Carlos M. Travieso, Jesús B. Alonso, Aythami Morales, Moises Díaz, J. Francisco Vargas, Patricia Henríquez, Réjean Plamondon, Umapada Pal, Abhijit Das and Michael Blumenstein. Their work appears in journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and CHEST Journal.
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.