Alejandro Mora-Rubio
Impact in
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- Advanced Steganography and Watermarking Techniques
- Digital Media Forensic Detection
- Generative Adversarial Networks and Image Synthesis
- Chaos-based Image/Signal Encryption
Papers in
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- Generative Adversarial Networks and Image Synthesis 3
- Advanced Steganography and Watermarking Techniques 3
- Digital Media Forensic Detection 3
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- AI in cancer detection 4
- Co-authors
- Reinel Tabares-Soto (11 shared papers)Mario Alejandro Bravo-Ortíz (10 shared papers)Harold Brayan Arteaga-Arteaga (9 shared papers)Simón Orozco-Arias (8 shared papers)Jesús Alejandro Alzate-Grisales (9 shared papers)Gustavo Isaza (3 shared papers)Oscar Cardona-Morales (3 shared papers)María de la Iglesia-Vayá (3 shared papers)
In The Last Decade
Alejandro Mora-Rubio
11 papers receiving 261 citations
Peers
Comparison fields: 5 of 59
- Health Informatics 9
- Computer Vision and Pattern Recognition 97
- Radiology, Nuclear Medicine and Imaging 72
- Neurology 24
- Artificial Intelligence 79
Countries citing papers authored by Alejandro Mora-Rubio
This map shows the geographic impact of Alejandro Mora-Rubio'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 Alejandro Mora-Rubio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alejandro Mora-Rubio more than expected).
Fields of papers citing papers by Alejandro Mora-Rubio
This network shows the impact of papers produced by Alejandro Mora-Rubio. 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 Alejandro Mora-Rubio. The network helps show where Alejandro Mora-Rubio may publish in the future.
Co-authors
The 14 scholars most cited alongside Alejandro Mora-Rubio, 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 | 2021 | 66 | |
| 2 | 2021 | 63 | |
| 3 | 2021 | 28 | |
| 4 | 2021 | 25 | |
| 5 | 2022 | 24 | |
| 6 | 2023 | 21 | |
| 7 | 2021 | 16 | |
| 8 | 2021 | 12 | |
| 9 | 2023 | 8 | |
| 10 | 2024 | 6 | |
| 11 | 2022 | 1 | |
| 12 | 2026 | 0 |
About Alejandro Mora-Rubio
Alejandro Mora-Rubio is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Neurology, having authored 12 papers that have together received 270 indexed citations. Recurring topics across this work include AI in cancer detection (4 papers), Generative Adversarial Networks and Image Synthesis (3 papers), Advanced Steganography and Watermarking Techniques (3 papers), Digital Media Forensic Detection (3 papers), Brain Tumor Detection and Classification (2 papers), Prostate Cancer Diagnosis and Treatment (2 papers), COVID-19 diagnosis using AI (2 papers) and Radiomics and Machine Learning in Medical Imaging (1 paper). The work is most often cited by research in Health Informatics (9 citations), Computer Vision and Pattern Recognition (97 citations), Radiology, Nuclear Medicine and Imaging (72 citations), Neurology (24 citations) and Artificial Intelligence (79 citations). Alejandro Mora-Rubio has collaborated with scholars based in Colombia, Spain and Chile. Frequent co-authors include Reinel Tabares-Soto, Mario Alejandro Bravo-Ortíz, Harold Brayan Arteaga-Arteaga, Simón Orozco-Arias, Jesús Alejandro Alzate-Grisales, Gustavo Isaza, Oscar Cardona-Morales, María de la Iglesia-Vayá, Raúl Ramos-Pollán and Gonzalo A. Ruz. Their work appears in journals such as PeerJ Computer Science, IEEE Access, Scientific Reports, Computers, materials & continua/Computers, materials & continua (Print) and Neural Computing and Applications.
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.