Rafael C. Carrasco
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Computational Theory and Mathematics top 5%
- Signal Processing top 10%
- Information Systems top 10%
- Co-authors
- José OncinaColin de la HigueraEnrique VidalFranck ThollardFrancisco CasacubertaMikel L. ForcadaLuisa MicóFelipe Sánchez-Martínez
- Topics
- Natural Language Processing Techniques (15 papers)Algorithms and Data Compression (13 papers)Machine Learning and Algorithms (7 papers)
In The Last Decade
Rafael C. Carrasco
34 papers receiving 627 citations
Peers
Comparison fields: 5 of 92
- Artificial Intelligence 467
- Computer Vision and Pattern Recognition 147
- Computational Theory and Mathematics 138
- Signal Processing 98
- Information Systems 89
Countries citing papers authored by Rafael C. Carrasco
This map shows the geographic impact of Rafael C. Carrasco'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 Rafael C. Carrasco with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rafael C. Carrasco more than expected).
Fields of papers citing papers by Rafael C. Carrasco
This network shows the impact of papers produced by Rafael C. Carrasco. 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 Rafael C. Carrasco. The network helps show where Rafael C. Carrasco may publish in the future.
Co-authorship network of co-authors of Rafael C. Carrasco
This figure shows the co-authorship network connecting the top 25 collaborators of Rafael C. Carrasco. A scholar is included among the top collaborators of Rafael C. Carrasco 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 Rafael C. Carrasco. Rafael C. Carrasco 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 | 2 | |
| 3 | 19 | |
| 4 | 21 | |
| 5 | 8 | |
| 6 | 3 | |
| 7 | 40 | |
| 8 | 8 | |
| 9 | 178 | |
| 10 | 2 | |
| 11 | 8 | |
| 12 | 3 | |
| 13 | 19 | |
| 14 | Encoding of sequential translators in discrete-time recurrent neural nets. | 2 |
| 15 | 62 | |
| 16 | 14 | |
| 17 | 23 | |
| 18 | Grammatical inference and applications : second International Colloquium, ICGI-94, Alicante, Spain, September 21-23, 1994 : proceedings | 1 |
| 19 | 42 | |
| 20 | Proceedings of the Second International Colloquium on Grammatical Inference and Applications | 2 |
About Rafael C. Carrasco
Rafael C. Carrasco is a scholar working on Artificial Intelligence, Conservation and Computational Theory and Mathematics, having authored 36 papers that have together received 683 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (15 papers), Algorithms and Data Compression (13 papers) and Machine Learning and Algorithms (7 papers). The work is most often cited by research in Artificial Intelligence (467 citations), Software (37 citations) and Signal Processing (98 citations). Rafael C. Carrasco has collaborated with scholars based in Spain, France and Italy. Frequent co-authors include José Oncina, Colin de la Higuera, Enrique Vidal, Franck Thollard, Francisco Casacuberta, Mikel L. Forcada, Luisa Micó, Felipe Sánchez-Martínez, Juan Ramón Rico-Juan and Jan Daciuk. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition 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.