Matteo Stefanini
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging
- Cognitive Neuroscience
- Molecular Biology
- Co-authors
- Rita CucchiaraLorenzo BaraldiMarcella CorniaSilvia CascianelliGiuseppe FiameniMassimiliano CorsiniElisa FicarraNicola Messina
- Topics
- Multimodal Machine Learning Applications (4 papers)Advanced Image and Video Retrieval Techniques (3 papers)Video Analysis and Summarization (2 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligencePattern Recognition LettersComputer Methods and Programs in Biomedicine
- Partner nations
- Italy
In The Last Decade
Matteo Stefanini
6 papers receiving 248 citations
Hit Papers
Peers
Comparison fields: 5 of 52
- Computer Vision and Pattern Recognition 209
- Artificial Intelligence 108
- Radiology, Nuclear Medicine and Imaging 11
- Cognitive Neuroscience 8
- Molecular Biology 7
Countries citing papers authored by Matteo Stefanini
This map shows the geographic impact of Matteo Stefanini'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 Stefanini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matteo Stefanini more than expected).
Fields of papers citing papers by Matteo Stefanini
This network shows the impact of papers produced by Matteo Stefanini. 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 Stefanini. The network helps show where Matteo Stefanini may publish in the future.
Co-authorship network of co-authors of Matteo Stefanini
This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Stefanini. A scholar is included among the top collaborators of Matteo Stefanini 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 Stefanini. Matteo Stefanini 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 | 11 | |
| 3 | From Show to Tell: A Survey on Deep Learning-Based Image Captioningbreakdown → | 198 |
| 4 | 18 | |
| 5 | 4 | |
| 6 | 18 |
About Matteo Stefanini
Matteo Stefanini is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems, having authored 6 papers that have together received 255 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (4 papers), Advanced Image and Video Retrieval Techniques (3 papers) and Video Analysis and Summarization (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (209 citations), Health Informatics (6 citations) and Artificial Intelligence (108 citations). Matteo Stefanini has collaborated with scholars based in Italy. Frequent co-authors include Rita Cucchiara, Lorenzo Baraldi, Marcella Cornia, Silvia Cascianelli, Giuseppe Fiameni, Massimiliano Corsini, Elisa Ficarra, Nicola Messina, Giuseppe Amato and Fabrizio Falchi. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition Letters and Computer Methods and Programs in Biomedicine.
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.