Isaac Triguero
- Artificial Intelligence top 0.5%
- Computer Vision and Pattern Recognition top 1%
- Signal Processing top 1%
- Information Systems top 1%
- Electrical and Electronic Engineering top 10%
- Co-authors
- Francisco HerreraSalvador GarcíaJesús MailloDaniel PeraltaJosé M. BenítezJulián LuengoEnrique OnievaÁngel Conde
- Topics
- Machine Learning and Data Classification (38 papers)Imbalanced Data Classification Techniques (18 papers)Evolutionary Algorithms and Applications (13 papers)
- Journals
- Monthly Notices of the Royal Astronomical SocietyExpert Systems with ApplicationsIEEE Access
- Partner nations
- SpainUnited KingdomBelgium
In The Last Decade
Isaac Triguero
88 papers receiving 3.4k citations
Hit Papers
Peers
Comparison fields: 5 of 160
- Artificial Intelligence 2.2k
- Computer Vision and Pattern Recognition 772
- Signal Processing 562
- Information Systems 525
- Electrical and Electronic Engineering 363
Countries citing papers authored by Isaac Triguero
This map shows the geographic impact of Isaac Triguero'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 Isaac Triguero with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Isaac Triguero more than expected).
Fields of papers citing papers by Isaac Triguero
This network shows the impact of papers produced by Isaac Triguero. 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 Isaac Triguero. The network helps show where Isaac Triguero may publish in the future.
Co-authorship network of co-authors of Isaac Triguero
This figure shows the co-authorship network connecting the top 25 collaborators of Isaac Triguero. A scholar is included among the top collaborators of Isaac Triguero 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 Isaac Triguero. Isaac Triguero 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 | 29 | |
| 5 | 3 | |
| 6 | 2 | |
| 7 | 5 | |
| 8 | 19 | |
| 9 | 20 | |
| 10 | 40 | |
| 11 | 2 | |
| 12 | 139 | |
| 13 | 18 | |
| 14 | 210 | |
| 15 | 224 | |
| 16 | 32 | |
| 17 | 24 | |
| 18 | 2 | |
| 19 | 47 | |
| 20 | 32 |
About Isaac Triguero
Isaac Triguero is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition, having authored 90 papers that have together received 3.5k indexed citations. Recurring topics across this work include Machine Learning and Data Classification (38 papers), Imbalanced Data Classification Techniques (18 papers) and Evolutionary Algorithms and Applications (13 papers). The work is most often cited by research in Artificial Intelligence (2.2k citations), Signal Processing (562 citations) and Computer Vision and Pattern Recognition (772 citations). Isaac Triguero has collaborated with scholars based in Spain, United Kingdom and Belgium. Frequent co-authors include Francisco Herrera, Salvador García, Jesús Maillo, Daniel Peralta, José M. Benítez, Julián Luengo, Enrique Onieva, Ángel Conde, Sergio Andrés Osuna Ramírez and Joaquín Derrac. Their work appears in journals such as Monthly Notices of the Royal Astronomical Society, Expert Systems with Applications and IEEE Access.
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.