Marcos Martinez‐Diaz
- Computer Vision and Pattern Recognition top 2%
- Signal Processing top 2%
- Information Systems top 2%
- Artificial Intelligence top 10%
- Human-Computer Interaction top 5%
- Co-authors
- Julián FiérrezJavier GalballyJavier Ortega-GarcíaFernando Alonso‐FernandezAythami MoralesEmanuele MaioranaPatrizio CampisiAlessandro Neri
- Topics
- User Authentication and Security Systems (14 papers)Biometric Identification and Security (14 papers)Handwritten Text Recognition Techniques (13 papers)
In The Last Decade
Marcos Martinez‐Diaz
24 papers receiving 582 citations
Peers
Comparison fields: 5 of 44
- Computer Vision and Pattern Recognition 401
- Signal Processing 389
- Information Systems 343
- Artificial Intelligence 93
- Human-Computer Interaction 92
Countries citing papers authored by Marcos Martinez‐Diaz
This map shows the geographic impact of Marcos Martinez‐Diaz'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 Marcos Martinez‐Diaz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcos Martinez‐Diaz more than expected).
Fields of papers citing papers by Marcos Martinez‐Diaz
This network shows the impact of papers produced by Marcos Martinez‐Diaz. 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 Marcos Martinez‐Diaz. The network helps show where Marcos Martinez‐Diaz may publish in the future.
Co-authorship network of co-authors of Marcos Martinez‐Diaz
This figure shows the co-authorship network connecting the top 25 collaborators of Marcos Martinez‐Diaz. A scholar is included among the top collaborators of Marcos Martinez‐Diaz 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 Marcos Martinez‐Diaz. Marcos Martinez‐Diaz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 62 | |
| 2 | 30 | |
| 3 | 37 | |
| 4 | 28 | |
| 5 | 8 | |
| 6 | 27 | |
| 7 | 48 | |
| 8 | 3 | |
| 9 | 4 | |
| 10 | 2 | |
| 11 | 15 | |
| 12 | 38 | |
| 13 | 7 | |
| 14 | 6 | |
| 15 | 47 | |
| 16 | 24 | |
| 17 | 11 | |
| 18 | 17 | |
| 19 | 16 | |
| 20 | 38 |
About Marcos Martinez‐Diaz
Marcos Martinez‐Diaz is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Information Systems, having authored 24 papers that have together received 610 indexed citations. Recurring topics across this work include User Authentication and Security Systems (14 papers), Biometric Identification and Security (14 papers) and Handwritten Text Recognition Techniques (13 papers). The work is most often cited by research in Signal Processing (389 citations), Computer Vision and Pattern Recognition (401 citations) and Human-Computer Interaction (92 citations). Marcos Martinez‐Diaz has collaborated with scholars based in Spain, Italy and Canada. Frequent co-authors include Julián Fiérrez, Javier Galbally, Javier Ortega-García, Fernando Alonso‐Fernandez, Aythami Morales, Emanuele Maiorana, Patrizio Campisi, Alessandro Neri, Juan A. Sigüenza and Manuel Freire. Their work appears in journals such as PLoS ONE, IEEE Access and Pattern Recognition.
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.