Javier Sánchez‐Monedero
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 5%
- Sociology and Political Science
- Electrical and Electronic Engineering
- Co-authors
- César Hervás‐MartínezPedro Antonio GutiérrezFrancisco Fernández‐NavarroMaría Pérez‐OrtizLina DencikM. Cruz-RamírezLilian EdwardsAurora Sáez
- Topics
- Neural Networks and Applications (7 papers)Imbalanced Data Classification Techniques (7 papers)Face and Expression Recognition (6 papers)
- Partner nations
- SpainUnited KingdomUnited States
In The Last Decade
Javier Sánchez‐Monedero
34 papers receiving 867 citations
Hit Papers
Peers
Comparison fields: 5 of 130
- Artificial Intelligence 450
- Computer Vision and Pattern Recognition 154
- Information Systems 113
- Sociology and Political Science 94
- Electrical and Electronic Engineering 77
Countries citing papers authored by Javier Sánchez‐Monedero
This map shows the geographic impact of Javier Sánchez‐Monedero'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 Javier Sánchez‐Monedero with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Javier Sánchez‐Monedero more than expected).
Fields of papers citing papers by Javier Sánchez‐Monedero
This network shows the impact of papers produced by Javier Sánchez‐Monedero. 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 Javier Sánchez‐Monedero. The network helps show where Javier Sánchez‐Monedero may publish in the future.
Co-authorship network of co-authors of Javier Sánchez‐Monedero
This figure shows the co-authorship network connecting the top 25 collaborators of Javier Sánchez‐Monedero. A scholar is included among the top collaborators of Javier Sánchez‐Monedero 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 Javier Sánchez‐Monedero. Javier Sánchez‐Monedero is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 8 | |
| 3 | 82 | |
| 4 | ORCA: A Matlab/Octave Toolbox for Ordinal Regression | 11 |
| 5 | 3 | |
| 6 | How to (partially) evaluate automated decision systems | 1 |
| 7 | 16 | |
| 8 | 3 | |
| 9 | Ordinal Regression Methods: Survey and Experimental Studybreakdown → | 281 |
| 10 | 5 | |
| 11 | 54 | |
| 12 | 32 | |
| 13 | Multi-scale Support Vector Machine Optimization by Kernel Target-Alignment. | 1 |
| 14 | 21 | |
| 15 | 18 | |
| 16 | 17 | |
| 17 | 18 | |
| 18 | 1 | |
| 19 | 58 | |
| 20 | 1 |
About Javier Sánchez‐Monedero
Javier Sánchez‐Monedero is a scholar working on Health Informatics, Artificial Intelligence and Safety Research, having authored 35 papers that have together received 892 indexed citations. Recurring topics across this work include Neural Networks and Applications (7 papers), Imbalanced Data Classification Techniques (7 papers) and Face and Expression Recognition (6 papers). The work is most often cited by research in Health Informatics (19 citations), Artificial Intelligence (450 citations) and Computer Vision and Pattern Recognition (154 citations). Javier Sánchez‐Monedero has collaborated with scholars based in Spain, United Kingdom and United States. Frequent co-authors include César Hervás‐Martínez, Pedro Antonio Gutiérrez, Francisco Fernández‐Navarro, María Pérez‐Ortiz, Lina Dencik, M. Cruz-Ramírez, Lilian Edwards, Aurora Sáez, Sancho Salcedo‐Sanz and C. Casanova‐Mateo. Their work appears in journals such as Nature Communications, IEEE Transactions on Medical Imaging and Neural Computation.
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.