R. Díaz Hernández
- Biophysics top 10%
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- Digital Imaging for Blood Diseases 5
- Medical Image Segmentation Techniques 2
- Advanced Neural Network Applications 2
- Face and Expression Recognition 2
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- AI in cancer detection 3
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- Infrared Thermography in Medicine 2
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- Blind Source Separation Techniques 2
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- Spectroscopy and Chemometric Analyses 2
R. Díaz Hernández
19 papers receiving 175 citations
Peers
Comparison fields: 5 of 57
- Biophysics 43
- Computer Vision and Pattern Recognition 122
- Media Technology 19
- Artificial Intelligence 69
- 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
The 15 scholars most cited alongside R. Díaz Hernández, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 0 | |
| 6 | 2022 | 3 | |
| 7 | 2018 | 2 | |
| 8 | 2018 | 3 | |
| 9 | 2016 | 4 | |
| 10 | 2015 | 63 | |
| 11 | 2015 | 12 | |
| 12 | 2014 | 17 | |
| 13 | 2014 | 5 | |
| 14 | A Hierarchical Model for Morphological Galaxy Classification. | 2013 | 10 |
| 15 | 2011 | 11 | |
| 16 | 2011 | 3 | |
| 17 | 2011 | 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 | 2010 | 3 |
| 19 | Segmentation of Bone Marrow Cell Images for Morphological Classification of Acute Leukemia | 2010 | 38 |
| 20 | A Supervised Method for Microcalcifications Detection using Breast Density | 2010 | 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), Medical Image Segmentation Techniques (2 papers), Advanced Neural Network Applications (2 papers), Blind Source Separation Techniques (2 papers), Spectroscopy and Chemometric Analyses (2 papers), Infrared Thermography in Medicine (2 papers) and Face and Expression Recognition (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.
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.