Carolina Reta
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Biophysics top 5%
- Radiology, Nuclear Medicine and Imaging
- Aerospace Engineering
- Co-authors
- Jesús A. GonzálezJosé Antonio Cantoral-CeballosLeopoldo Altamirano-RoblesLeonor Adriana Cárdenas-RobledoR. Díaz HernándezLuis Enrique SucarHind TaudJuan Irving Vasquez-Gomez
- Topics
- Digital Imaging for Blood Diseases (5 papers)AI in cancer detection (2 papers)Chaos-based Image/Signal Encryption (2 papers)
- Partner nations
- MexicoUnited KingdomParaguay
In The Last Decade
Carolina Reta
14 papers receiving 355 citations
Peers
Comparison fields: 5 of 75
- Computer Vision and Pattern Recognition 266
- Artificial Intelligence 114
- Biophysics 55
- Radiology, Nuclear Medicine and Imaging 41
- Aerospace Engineering 41
Countries citing papers authored by Carolina Reta
This map shows the geographic impact of Carolina Reta'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 Carolina Reta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carolina Reta more than expected).
Fields of papers citing papers by Carolina Reta
This network shows the impact of papers produced by Carolina Reta. 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 Carolina Reta. The network helps show where Carolina Reta may publish in the future.
Co-authorship network of co-authors of Carolina Reta
This figure shows the co-authorship network connecting the top 25 collaborators of Carolina Reta. A scholar is included among the top collaborators of Carolina Reta 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 Carolina Reta. Carolina Reta 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 | 1 | |
| 3 | 83 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 59 | |
| 7 | 10 | |
| 8 | 11 | |
| 9 | 63 | |
| 10 | 1 | |
| 11 | 1 | |
| 12 | 62 | |
| 13 | 11 | |
| 14 | 13 | |
| 15 | Segmentation of Bone Marrow Cell Images for Morphological Classification of Acute Leukemia | 38 |
| 16 | 12 | |
| 17 | 4 |
About Carolina Reta
Carolina Reta is a scholar working on Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering and Human-Computer Interaction, having authored 17 papers that have together received 370 indexed citations. Recurring topics across this work include Digital Imaging for Blood Diseases (5 papers), AI in cancer detection (2 papers) and Chaos-based Image/Signal Encryption (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (266 citations), Biophysics (55 citations) and Human-Computer Interaction (35 citations). Carolina Reta has collaborated with scholars based in Mexico, United Kingdom and Paraguay. Frequent co-authors include Jesús A. González, José Antonio Cantoral-Ceballos, Leopoldo Altamirano-Robles, Leonor Adriana Cárdenas-Robledo, R. Díaz Hernández, Luis Enrique Sucar, Hind Taud, Juan Irving Vasquez-Gomez, Miguel González-Mendoza and Alejandro Rosales-Pérez. Their work appears in journals such as PLoS ONE, Pattern Recognition Letters and Advances in experimental medicine and biology.
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.