Matteo Maggioni
- Computer Vision and Pattern Recognition top 5%
- Media Technology top 2%
- Computational Mechanics top 10%
- Biomedical Engineering
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Alessandro FoiKaren EgiazarianGiacomo BoracchiJ. Alison NobleAntonietta PepeJussi TohkaSylvia RuedaAris T. Papageorghiou
- Topics
- Image and Signal Denoising Methods (6 papers)Advanced Image Processing Techniques (6 papers)Advanced Image Fusion Techniques (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingThe Journal of Urology
- Partner nations
- SwedenUnited KingdomFinland
In The Last Decade
Matteo Maggioni
10 papers receiving 428 citations
Peers
Comparison fields: 5 of 63
- Computer Vision and Pattern Recognition 351
- Media Technology 164
- Computational Mechanics 66
- Biomedical Engineering 56
- Radiology, Nuclear Medicine and Imaging 34
Countries citing papers authored by Matteo Maggioni
This map shows the geographic impact of Matteo Maggioni'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 Matteo Maggioni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matteo Maggioni more than expected).
Fields of papers citing papers by Matteo Maggioni
This network shows the impact of papers produced by Matteo Maggioni. 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 Matteo Maggioni. The network helps show where Matteo Maggioni may publish in the future.
Co-authorship network of co-authors of Matteo Maggioni
This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Maggioni. A scholar is included among the top collaborators of Matteo Maggioni 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 Matteo Maggioni. Matteo Maggioni is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 4 | |
| 7 | 22 | |
| 8 | 3 | |
| 9 | 63 | |
| 10 | 258 | |
| 11 | 38 | |
| 12 | 48 |
About Matteo Maggioni
Matteo Maggioni is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Computer Graphics and Computer-Aided Design, having authored 12 papers that have together received 443 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (6 papers), Advanced Image Processing Techniques (6 papers) and Advanced Image Fusion Techniques (4 papers). The work is most often cited by research in Media Technology (164 citations), Computer Vision and Pattern Recognition (351 citations) and Computational Mathematics (5 citations). Matteo Maggioni has collaborated with scholars based in Sweden, United Kingdom and Finland. Frequent co-authors include Alessandro Foi, Karen Egiazarian, Giacomo Boracchi, J. Alison Noble, Antonietta Pepe, Jussi Tohka, Sylvia Rueda, Aris T. Papageorghiou, Yongxin Yang and Eduardo Pérez-Pellitero. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and The Journal of Urology.
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.