Andrea Ferracani
- Computer Vision and Pattern Recognition top 10%
- Human-Computer Interaction top 5%
- Artificial Intelligence
- Cognitive Neuroscience
- Information Systems
- Co-authors
- Alberto Del BimboMarco BertiniLorenzo SeidenariSvebor KaramanTiberio UricchioAndrew D. BagdanovGiuseppe SerraMarco Meoni
- Topics
- Video Analysis and Summarization (19 papers)Advanced Image and Video Retrieval Techniques (9 papers)Image Retrieval and Classification Techniques (9 papers)
In The Last Decade
Andrea Ferracani
34 papers receiving 249 citations
Peers
Comparison fields: 5 of 65
- Computer Vision and Pattern Recognition 118
- Human-Computer Interaction 101
- Artificial Intelligence 43
- Cognitive Neuroscience 39
- Information Systems 33
Countries citing papers authored by Andrea Ferracani
This map shows the geographic impact of Andrea Ferracani'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 Andrea Ferracani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrea Ferracani more than expected).
Fields of papers citing papers by Andrea Ferracani
This network shows the impact of papers produced by Andrea Ferracani. 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 Andrea Ferracani. The network helps show where Andrea Ferracani may publish in the future.
Co-authorship network of co-authors of Andrea Ferracani
This figure shows the co-authorship network connecting the top 25 collaborators of Andrea Ferracani. A scholar is included among the top collaborators of Andrea Ferracani 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 Andrea Ferracani. Andrea Ferracani 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 | 3 | |
| 3 | 1 | |
| 4 | 29 | |
| 5 | 1 | |
| 6 | 42 | |
| 7 | 10 | |
| 8 | 5 | |
| 9 | 12 | |
| 10 | 1 | |
| 11 | 6 | |
| 12 | 2 | |
| 13 | 3 | |
| 14 | 4 | |
| 15 | 10 | |
| 16 | 3 | |
| 17 | 5 | |
| 18 | 0 | |
| 19 | 3 | |
| 20 | 2 |
About Andrea Ferracani
Andrea Ferracani is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Geography, Planning and Development, having authored 37 papers that have together received 259 indexed citations. Recurring topics across this work include Video Analysis and Summarization (19 papers), Advanced Image and Video Retrieval Techniques (9 papers) and Image Retrieval and Classification Techniques (9 papers). The work is most often cited by research in Human-Computer Interaction (101 citations), Computer Vision and Pattern Recognition (118 citations) and Museology (18 citations). Andrea Ferracani has collaborated with scholars based in Italy, Spain and Austria. Frequent co-authors include Alberto Del Bimbo, Marco Bertini, Lorenzo Seidenari, Svebor Karaman, Tiberio Uricchio, Andrew D. Bagdanov, Giuseppe Serra, Marco Meoni, Federico Pernici and Pietro Pala. Their work appears in journals such as Multimedia Tools and Applications, ACM Transactions on Multimedia Computing Communications and Applications and Universal Access in the Information Society.
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.