Francesco Fontanella
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Molecular Biology
- Media Technology top 5%
- Neurology
- Co-authors
- Claudio De StefanoAlessandra Scotto di FrecaNicole Dalia CiliaClaudio MarroccoMario MolinaraGiuseppe PirloDonato ImpedovoL.P. Cordella
- Topics
- Handwritten Text Recognition Techniques (15 papers)Evolutionary Algorithms and Applications (9 papers)Metaheuristic Optimization Algorithms Research (8 papers)
- Partner nations
- ItalyNetherlandsPortugal
In The Last Decade
Francesco Fontanella
53 papers receiving 730 citations
Peers
Comparison fields: 5 of 121
- Computer Vision and Pattern Recognition 328
- Artificial Intelligence 323
- Molecular Biology 90
- Media Technology 79
- Neurology 49
Countries citing papers authored by Francesco Fontanella
This map shows the geographic impact of Francesco Fontanella'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 Francesco Fontanella with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Francesco Fontanella more than expected).
Fields of papers citing papers by Francesco Fontanella
This network shows the impact of papers produced by Francesco Fontanella. 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 Francesco Fontanella. The network helps show where Francesco Fontanella may publish in the future.
Co-authorship network of co-authors of Francesco Fontanella
This figure shows the co-authorship network connecting the top 25 collaborators of Francesco Fontanella. A scholar is included among the top collaborators of Francesco Fontanella 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 Francesco Fontanella. Francesco Fontanella 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 | 12 | |
| 5 | 5 | |
| 6 | 4 | |
| 7 | 17 | |
| 8 | 17 | |
| 9 | 6 | |
| 10 | 34 | |
| 11 | 16 | |
| 12 | 3 | |
| 13 | 11 | |
| 14 | 9 | |
| 15 | 105 | |
| 16 | 1 | |
| 17 | 1 | |
| 18 | 3 | |
| 19 | 17 | |
| 20 | 2 |
About Francesco Fontanella
Francesco Fontanella is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 57 papers that have together received 764 indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (15 papers), Evolutionary Algorithms and Applications (9 papers) and Metaheuristic Optimization Algorithms Research (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (328 citations), Artificial Intelligence (323 citations) and Media Technology (79 citations). Francesco Fontanella has collaborated with scholars based in Italy, Netherlands and Portugal. Frequent co-authors include Claudio De Stefano, Alessandra Scotto di Freca, Nicole Dalia Cilia, Claudio Marrocco, Mario Molinara, Giuseppe Pirlo, Donato Impedovo, L.P. Cordella, Marilena Maniaci and Angelo Marcelli. Their work appears in journals such as IEEE Access, Information Sciences and Applied Soft Computing.
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.