C. Caraffi
- Computer Vision and Pattern Recognition top 2%
- Automotive Engineering top 5%
- Aerospace Engineering top 10%
- Environmental Engineering top 10%
- Electrical and Electronic Engineering
- Co-authors
- Alberto BroggiPaolo GrisleriPier Paolo PortaRean Isabella FedrigaSilvia CattaniPaolo ZaniJ ŠochmanJiřı́ Matas
- Topics
- Video Surveillance and Tracking Methods (6 papers)Autonomous Vehicle Technology and Safety (5 papers)Robotics and Sensor-Based Localization (4 papers)
- Journals
- IEEE Transactions on Intelligent Transportation SystemsComputer Vision and Image UnderstandingPadua Research Archive (University of Padova)
- Partner nations
- ItalySwitzerlandUnited States
In The Last Decade
C. Caraffi
10 papers receiving 493 citations
Peers
Comparison fields: 5 of 46
- Computer Vision and Pattern Recognition 421
- Automotive Engineering 257
- Aerospace Engineering 150
- Environmental Engineering 72
- Electrical and Electronic Engineering 63
Countries citing papers authored by C. Caraffi
This map shows the geographic impact of C. Caraffi'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 C. Caraffi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites C. Caraffi more than expected).
Fields of papers citing papers by C. Caraffi
This network shows the impact of papers produced by C. Caraffi. 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 C. Caraffi. The network helps show where C. Caraffi may publish in the future.
Co-authorship network of co-authors of C. Caraffi
This figure shows the co-authorship network connecting the top 25 collaborators of C. Caraffi. A scholar is included among the top collaborators of C. Caraffi 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 C. Caraffi. C. Caraffi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 100 | |
| 2 | 53 | |
| 3 | 11 | |
| 4 | 19 | |
| 5 | 11 | |
| 6 | 83 | |
| 7 | 63 | |
| 8 | 75 | |
| 9 | 112 | |
| 10 | 3 |
About C. Caraffi
C. Caraffi is a scholar working on Automotive Engineering, Computer Vision and Pattern Recognition and Environmental Engineering, having authored 10 papers that have together received 530 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (6 papers), Autonomous Vehicle Technology and Safety (5 papers) and Robotics and Sensor-Based Localization (4 papers). The work is most often cited by research in Automotive Engineering (257 citations), Computer Vision and Pattern Recognition (421 citations) and Aerospace Engineering (150 citations). C. Caraffi has collaborated with scholars based in Italy, Switzerland and United States. Frequent co-authors include Alberto Broggi, Paolo Grisleri, Pier Paolo Porta, Rean Isabella Fedriga, Silvia Cattani, Paolo Zani, J Šochman, Jiřı́ Matas, Michael Del Rose and Massimo Bertozzi. Their work appears in journals such as IEEE Transactions on Intelligent Transportation Systems, Computer Vision and Image Understanding and Padua Research Archive (University of Padova).
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.