Stefano Cagnoni
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Biomedical Engineering top 10%
- Cardiology and Cardiovascular Medicine top 10%
- Computational Theory and Mathematics top 5%
- Co-authors
- Riccardo PoliG. ValliMonica MordoniniLuca MussiFabio DaolioPablo MesejoGuido MatrellaIlaria De Munari
- Topics
- Evolutionary Algorithms and Applications (29 papers)Metaheuristic Optimization Algorithms Research (22 papers)Advanced Image and Video Retrieval Techniques (13 papers)
- Partner nations
- ItalyUnited KingdomSpain
In The Last Decade
Stefano Cagnoni
112 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 156
- Artificial Intelligence 631
- Computer Vision and Pattern Recognition 522
- Biomedical Engineering 315
- Cardiology and Cardiovascular Medicine 195
- Computational Theory and Mathematics 175
Countries citing papers authored by Stefano Cagnoni
This map shows the geographic impact of Stefano Cagnoni'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 Stefano Cagnoni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefano Cagnoni more than expected).
Fields of papers citing papers by Stefano Cagnoni
This network shows the impact of papers produced by Stefano Cagnoni. 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 Stefano Cagnoni. The network helps show where Stefano Cagnoni may publish in the future.
Co-authorship network of co-authors of Stefano Cagnoni
This figure shows the co-authorship network connecting the top 25 collaborators of Stefano Cagnoni. A scholar is included among the top collaborators of Stefano Cagnoni 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 Stefano Cagnoni. Stefano Cagnoni is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 8 | |
| 7 | 24 | |
| 8 | 13 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 19 | |
| 12 | 3 | |
| 13 | 8 | |
| 14 | 11 | |
| 15 | 1 | |
| 16 | 60 | |
| 17 | 23 | |
| 18 | 29 | |
| 19 | Applications of Evolutionary Computing: Evoworkshops 2003 | 49 |
| 20 | Real-world applications of evolutionary computing : EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoRob, and EvoFlight, Edinburgh, Scotland, UK, April 17, 2000 : proceedings | 2 |
About Stefano Cagnoni
Stefano Cagnoni is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 116 papers that have together received 1.8k indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (29 papers), Metaheuristic Optimization Algorithms Research (22 papers) and Advanced Image and Video Retrieval Techniques (13 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (522 citations), Artificial Intelligence (631 citations) and Media Technology (108 citations). Stefano Cagnoni has collaborated with scholars based in Italy, United Kingdom and Spain. Frequent co-authors include Riccardo Poli, G. Valli, Monica Mordonini, Luca Mussi, Fabio Daolio, Pablo Mesejo, Guido Matrella, Ilaria De Munari, Paolo Ciampolini and Giovanni Adorni. Their work appears in journals such as PLoS ONE, IEEE Access and IEEE Transactions on Biomedical Engineering.
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.