Claudio De Stefano
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Computational Theory and Mathematics top 5%
- Molecular Biology
- Media Technology top 5%
- Co-authors
- Francesco FontanellaAlessandra Scotto di FrecaAngelo MarcelliNicole Dalia CiliaM. VentoAntonio Della CioppaCarlo SansoneClaudio Marrocco
- Topics
- Handwritten Text Recognition Techniques (31 papers)Neural Networks and Applications (18 papers)Image Retrieval and Classification Techniques (15 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessPattern Recognition
- Partner nations
- ItalyNetherlandsPortugal
In The Last Decade
Claudio De Stefano
83 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 119
- Artificial Intelligence 610
- Computer Vision and Pattern Recognition 477
- Computational Theory and Mathematics 125
- Molecular Biology 104
- Media Technology 99
Countries citing papers authored by Claudio De Stefano
This map shows the geographic impact of Claudio De Stefano'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 Claudio De Stefano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Claudio De Stefano more than expected).
Fields of papers citing papers by Claudio De Stefano
This network shows the impact of papers produced by Claudio De Stefano. 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 Claudio De Stefano. The network helps show where Claudio De Stefano may publish in the future.
Co-authorship network of co-authors of Claudio De Stefano
This figure shows the co-authorship network connecting the top 25 collaborators of Claudio De Stefano. A scholar is included among the top collaborators of Claudio De Stefano 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 Claudio De Stefano. Claudio De Stefano is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 5 | |
| 5 | 4 | |
| 6 | 17 | |
| 7 | 6 | |
| 8 | 34 | |
| 9 | 105 | |
| 10 | 2 | |
| 11 | 2 | |
| 12 | 1 | |
| 13 | 1 | |
| 14 | 2 | |
| 15 | 59 | |
| 16 | 1 | |
| 17 | 5 | |
| 18 | 3 | |
| 19 | 57 | |
| 20 | 2 |
About Claudio De Stefano
Claudio De Stefano is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Human-Computer Interaction, having authored 90 papers that have together received 1.2k indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (31 papers), Neural Networks and Applications (18 papers) and Image Retrieval and Classification Techniques (15 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (477 citations), Artificial Intelligence (610 citations) and Media Technology (99 citations). Claudio De Stefano has collaborated with scholars based in Italy, Netherlands and Portugal. Frequent co-authors include Francesco Fontanella, Alessandra Scotto di Freca, Angelo Marcelli, Nicole Dalia Cilia, M. Vento, Antonio Della Cioppa, Carlo Sansone, Claudio Marrocco, L.P. Cordella and Giuseppe Pirlo. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Pattern Recognition.
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.