Aníbal Pedraza
Impact in
- Biophysics top 10%
- Cell Image Analysis Techniques
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- Digital Imaging for Blood Diseases
Papers in
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- Adversarial Robustness in Machine Learning 10
- Anomaly Detection Techniques and Applications 6
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- Digital Imaging for Blood Diseases 4
- Co-authors
- Gloria Bueno (22 shared papers)Óscar Déniz (19 shared papers)María Borrego‐Ramos (4 shared papers)Gabriel Cristóbal (4 shared papers)Saúl Blanco (4 shared papers)Jesús Ruiz-Santaquiteria (7 shared papers)Jesús Salido (3 shared papers)Jaime Gallego (1 shared paper)
In The Last Decade
Aníbal Pedraza
20 papers receiving 393 citations
Peers
Comparison fields: 5 of 93
- Biophysics 42
- Computer Vision and Pattern Recognition 129
- Media Technology 51
- Artificial Intelligence 130
- Water Science and Technology 39
Countries citing papers authored by Aníbal Pedraza
This map shows the geographic impact of Aníbal Pedraza'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 Aníbal Pedraza with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aníbal Pedraza more than expected).
Fields of papers citing papers by Aníbal Pedraza
This network shows the impact of papers produced by Aníbal Pedraza. 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 Aníbal Pedraza. The network helps show where Aníbal Pedraza may publish in the future.
Co-authors
The 20 scholars most cited alongside Aníbal Pedraza, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 91 | |
| 2 | 2018 | 66 | |
| 3 | 2023 | 51 | |
| 4 | 2017 | 49 | |
| 5 | 2020 | 25 | |
| 6 | 2018 | 22 | |
| 7 | 2017 | 22 | |
| 8 | 2022 | 13 | |
| 9 | 2021 | 10 | |
| 10 | 2021 | 10 | |
| 11 | 2020 | 9 | |
| 12 | 2022 | 8 | |
| 13 | 2024 | 7 | |
| 14 | 2023 | 5 | |
| 15 | 2022 | 3 | |
| 16 | 2022 | 3 | |
| 17 | 2024 | 2 | |
| 18 | 2025 | 2 | |
| 19 | 2024 | 1 | |
| 20 | 2022 | 1 |
About Aníbal Pedraza
Aníbal Pedraza is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Molecular Biology and Hardware and Architecture, having authored 23 papers that have together received 400 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (10 papers), Anomaly Detection Techniques and Applications (6 papers), Digital Imaging for Blood Diseases (4 papers), Physical Unclonable Functions (PUFs) and Hardware Security (4 papers), COVID-19 diagnosis using AI (3 papers), Cell Image Analysis Techniques (3 papers), Identification and Quantification in Food (3 papers) and Diatoms and Algae Research (3 papers). The work is most often cited by research in Biophysics (42 citations), Computer Vision and Pattern Recognition (129 citations), Media Technology (51 citations), Artificial Intelligence (130 citations) and Water Science and Technology (39 citations). Aníbal Pedraza has collaborated with scholars based in Spain, Germany and Italy. Frequent co-authors include Gloria Bueno, Óscar Déniz, María Borrego‐Ramos, Gabriel Cristóbal, Saúl Blanco, Jesús Ruiz-Santaquiteria, Jesús Salido, Jaime Gallego, Georg Steiner and Noelia Vállez. Their work appears in journals such as International Journal of Machine Learning and Cybernetics, Applied Sciences, Chaos Solitons & Fractals, Applied Intelligence and Digital Signal Processing.
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.