Claudio Piciarelli
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence top 2%
- Computer Networks and Communications top 5%
- Signal Processing top 5%
- Aerospace Engineering top 5%
- Co-authors
- Gian Luca ForestiChristian MicheloniNiki MartinelDaniele PannoneDanilo AvolaLuigi CinqueLauro SnidaroPankaj Kumar Mishra
- Topics
- Video Surveillance and Tracking Methods (20 papers)Anomaly Detection Techniques and Applications (13 papers)Time Series Analysis and Forecasting (10 papers)
In The Last Decade
Claudio Piciarelli
52 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 94
- Computer Vision and Pattern Recognition 876
- Artificial Intelligence 658
- Computer Networks and Communications 292
- Signal Processing 212
- Aerospace Engineering 199
Countries citing papers authored by Claudio Piciarelli
This map shows the geographic impact of Claudio Piciarelli'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 Claudio Piciarelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Claudio Piciarelli more than expected).
Fields of papers citing papers by Claudio Piciarelli
This network shows the impact of papers produced by Claudio Piciarelli. 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 Claudio Piciarelli. The network helps show where Claudio Piciarelli may publish in the future.
Co-authorship network of co-authors of Claudio Piciarelli
This figure shows the co-authorship network connecting the top 25 collaborators of Claudio Piciarelli. A scholar is included among the top collaborators of Claudio Piciarelli 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 Claudio Piciarelli. Claudio Piciarelli 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 | 1 | |
| 4 | 9 | |
| 5 | 71 | |
| 6 | 9 | |
| 7 | 26 | |
| 8 | 4 | |
| 9 | 43 | |
| 10 | 25 | |
| 11 | 56 | |
| 12 | 14 | |
| 13 | 27 | |
| 14 | Distributed signature fusion for person re-identification | 22 |
| 15 | 1 | |
| 16 | 13 | |
| 17 | 4 | |
| 18 | 37 | |
| 19 | 1 | |
| 20 | 1 |
About Claudio Piciarelli
Claudio Piciarelli is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Instrumentation, having authored 54 papers that have together received 1.4k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (20 papers), Anomaly Detection Techniques and Applications (13 papers) and Time Series Analysis and Forecasting (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (876 citations), Artificial Intelligence (658 citations) and Signal Processing (212 citations). Claudio Piciarelli has collaborated with scholars based in Italy and Austria. Frequent co-authors include Gian Luca Foresti, Christian Micheloni, Niki Martinel, Daniele Pannone, Danilo Avola, Luigi Cinque, Lauro Snidaro, Pankaj Kumar Mishra, Bernhard Rinner and Alessio Fagioli. Their work appears in journals such as International Journal of Molecular Sciences, IEEE Access and Sensors.
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.