Fabrício Breve
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Statistical and Nonlinear Physics top 10%
- Computer Networks and Communications
- Cognitive Neuroscience
- Co-authors
- Liang ZhaoMarcos G. QuilesElbert E. N. MacauJiming LiuWitold PedryczNelson D. A. MascarenhasMoacir Antonelli PontiDaniel Carlos Guimarães Pedronette
- Topics
- Face and Expression Recognition (9 papers)Machine Learning and Data Classification (8 papers)Neural dynamics and brain function (7 papers)
- Cited by
- Statistical and Nonlinear PhysicsArtificial IntelligenceComputer Vision and Pattern Recognition
In The Last Decade
Fabrício Breve
24 papers receiving 222 citations
Peers
Comparison fields: 5 of 61
- Artificial Intelligence 131
- Computer Vision and Pattern Recognition 72
- Statistical and Nonlinear Physics 61
- Computer Networks and Communications 37
- Cognitive Neuroscience 21
Countries citing papers authored by Fabrício Breve
This map shows the geographic impact of Fabrício Breve'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 Fabrício Breve with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabrício Breve more than expected).
Fields of papers citing papers by Fabrício Breve
This network shows the impact of papers produced by Fabrício Breve. 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 Fabrício Breve. The network helps show where Fabrício Breve may publish in the future.
Co-authorship network of co-authors of Fabrício Breve
This figure shows the co-authorship network connecting the top 25 collaborators of Fabrício Breve. A scholar is included among the top collaborators of Fabrício Breve 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 Fabrício Breve. Fabrício Breve 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 | 25 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | 3 | |
| 7 | 7 | |
| 8 | 3 | |
| 9 | 21 | |
| 10 | 3 | |
| 11 | 7 | |
| 12 | 49 | |
| 13 | 16 | |
| 14 | 39 | |
| 15 | 1 | |
| 16 | 2 | |
| 17 | 2 | |
| 18 | 5 | |
| 19 | 3 | |
| 20 | 4 |
About Fabrício Breve
Fabrício Breve is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cognitive Neuroscience, having authored 25 papers that have together received 227 indexed citations. Recurring topics across this work include Face and Expression Recognition (9 papers), Machine Learning and Data Classification (8 papers) and Neural dynamics and brain function (7 papers). The work is most often cited by research in Statistical and Nonlinear Physics (61 citations), Artificial Intelligence (131 citations) and Computer Vision and Pattern Recognition (72 citations). Fabrício Breve has collaborated with scholars based in Brazil, Canada and Moldova. Frequent co-authors include Liang Zhao, Marcos G. Quiles, Elbert E. N. Macau, Jiming Liu, Witold Pedrycz, Nelson D. A. Mascarenhas, Moacir Antonelli Ponti, Daniel Carlos Guimarães Pedronette, Roseli Aparecida Francelin Romero and Lucas Pascotti Valem. Their work appears in journals such as Expert Systems with Applications, Neurocomputing and IEEE Transactions on Knowledge and Data Engineering.
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.