R. Díaz Hernández
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Biophysics top 10%
- Plant Science
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Jesús A. GonzálezLeopoldo Altamirano-RoblesCarolina RetaHayde Peregrina‐BarretoMàrius Ramírez-CardonaLuis Enrique SucarGustavo Rodríguez‐GómezSaúl Zapotecas–Martínez
- Topics
- Digital Imaging for Blood Diseases (5 papers)AI in cancer detection (3 papers)Medical Image Segmentation Techniques (2 papers)
- Partner nations
- MexicoUnited StatesSouth Korea
In The Last Decade
R. Díaz Hernández
19 papers receiving 175 citations
Peers
Comparison fields: 5 of 57
- Computer Vision and Pattern Recognition 122
- Artificial Intelligence 69
- Biophysics 43
- Plant Science 26
- Radiology, Nuclear Medicine and Imaging 24
Countries citing papers authored by R. Díaz Hernández
This map shows the geographic impact of R. Díaz Hernández'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 R. Díaz Hernández with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites R. Díaz Hernández more than expected).
Fields of papers citing papers by R. Díaz Hernández
This network shows the impact of papers produced by R. Díaz Hernández. 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 R. Díaz Hernández. The network helps show where R. Díaz Hernández may publish in the future.
Co-authorship network of co-authors of R. Díaz Hernández
This figure shows the co-authorship network connecting the top 25 collaborators of R. Díaz Hernández. A scholar is included among the top collaborators of R. Díaz Hernández 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 R. Díaz Hernández. R. Díaz Hernández 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 | 1 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 2 | |
| 8 | 3 | |
| 9 | 4 | |
| 10 | 63 | |
| 11 | 12 | |
| 12 | 17 | |
| 13 | 5 | |
| 14 | A Hierarchical Model for Morphological Galaxy Classification. | 10 |
| 15 | 11 | |
| 16 | 3 | |
| 17 | 1 | |
| 18 | Scanning electron microscopy characterization of iron, nickel and sulfur in chondrules from the Allende meteorite - further evidence for between-chondrules major compositional differences | 3 |
| 19 | Segmentation of Bone Marrow Cell Images for Morphological Classification of Acute Leukemia | 38 |
| 20 | A Supervised Method for Microcalcifications Detection using Breast Density | 1 |
About R. Díaz Hernández
R. Díaz Hernández is a scholar working on Computer Vision and Pattern Recognition, Biophysics and Instrumentation, having authored 20 papers that have together received 181 indexed citations. Recurring topics across this work include Digital Imaging for Blood Diseases (5 papers), AI in cancer detection (3 papers) and Medical Image Segmentation Techniques (2 papers). The work is most often cited by research in Biophysics (43 citations), Computer Vision and Pattern Recognition (122 citations) and Media Technology (19 citations). R. Díaz Hernández has collaborated with scholars based in Mexico, United States and South Korea. Frequent co-authors include Jesús A. González, Leopoldo Altamirano-Robles, Carolina Reta, Hayde Peregrina‐Barreto, Màrius Ramírez-Cardona, Luis Enrique Sucar, Gustavo Rodríguez‐Gómez, Saúl Zapotecas–Martínez, Mehdi Hajinoroozi and Adol Esquivel. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Sensors.
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.