Fabio Scotti
Impact in
- Signal Processing top 0.5%
- Biometric Identification and Security
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- Digital Imaging for Blood Diseases
- Face recognition and analysis
Papers in
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- Biometric Identification and Security 50
-
- Face recognition and analysis 20
- Digital Imaging for Blood Diseases 11
- Co-authors
- Vincenzo PiuriRuggero Donida LabatiAngelo GenoveseRoberto SassiEnrique MuñozKonstantinos N. PlataniotisCesare AlippiGianluca Sforza
- Journals
- IEEE Access (10 papers)IEEE Transactions on Instrumentation and Measurement (9 papers)IEEE Transactions on Geoscience and Remote Sensing (6 papers)Pattern Recognition Letters (4 papers)IEEE Transactions on Systems Man and Cybernetics Systems (3 papers)
- Partner nations
- ItalyChinaUnited States
In The Last Decade
Fabio Scotti
150 papers receiving 3.3k citations
Peers
Comparison fields: 5 of 150
- Signal Processing 1.1k
- Computer Vision and Pattern Recognition 1.8k
- Biophysics 236
- Artificial Intelligence 915
- Information Systems 626
Countries citing papers authored by Fabio Scotti
This map shows the geographic impact of Fabio Scotti'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 Fabio Scotti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabio Scotti more than expected).
Fields of papers citing papers by Fabio Scotti
This network shows the impact of papers produced by Fabio Scotti. 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 Fabio Scotti. The network helps show where Fabio Scotti may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Fabio Scotti, 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 | 2025 | 0 | |
| 2 | 2025 | 3 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 2 | |
| 6 | 2023 | 3 | |
| 7 | 2023 | 3 | |
| 8 | 2022 | 2 | |
| 9 | 2021 | 6 | |
| 10 | 2021 | 29 | |
| 11 | 2021 | 20 | |
| 12 | 2021 | 18 | |
| 13 | 2021 | 11 | |
| 14 | 2020 | 10 | |
| 15 | 2020 | 7 | |
| 16 | 2018 | 26 | |
| 17 | 2018 | 257 | |
| 18 | 2018 | 9 | |
| 19 | 2016 | 4 | |
| 20 | 2014 | 31 |
About Fabio Scotti
Fabio Scotti is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering, Information Systems and Media Technology, having authored 161 papers that have together received 3.5k indexed citations. Recurring topics across this work include Biometric Identification and Security (50 papers), User Authentication and Security Systems (29 papers), Face recognition and analysis (20 papers), Industrial Vision Systems and Defect Detection (15 papers), Digital Imaging for Blood Diseases (11 papers), Forensic Fingerprint Detection Methods (9 papers), ECG Monitoring and Analysis (9 papers) and Neural Networks and Applications (9 papers). The work is most often cited by research in Signal Processing (1.1k citations), Computer Vision and Pattern Recognition (1.8k citations), Biophysics (236 citations), Artificial Intelligence (915 citations) and Information Systems (626 citations). Fabio Scotti has collaborated with scholars based in Italy, China and United States. Frequent co-authors include Vincenzo Piuri, Ruggero Donida Labati, Angelo Genovese, Roberto Sassi, Enrique Muñoz, Konstantinos N. Plataniotis, Cesare Alippi, Gianluca Sforza, Yikui Zhai and Subhas Chandra Mukhopadhyay. Their work appears in journals such as IEEE Access, IEEE Transactions on Instrumentation and Measurement, IEEE Transactions on Geoscience and Remote Sensing, Pattern Recognition Letters and IEEE Transactions on Systems Man and Cybernetics Systems.
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.