Vincenzo Piuri
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 0.5%
- Signal Processing top 0.5%
- Information Systems top 0.5%
- Electrical and Electronic Engineering top 5%
- Co-authors
- Fabio ScottiRuggero Donida LabatiAngelo GenoveseCesare AlippiRavi JhawarEnrique MuñozAlessandro FerreroLuca Breveglieri
- Topics
- Biometric Identification and Security (47 papers)Neural Networks and Applications (38 papers)VLSI and Analog Circuit Testing (31 papers)
- Journals
- IEEE Transactions on Geoscience and Remote SensingIEEE Transactions on Signal ProcessingIEEE Access
- Partner nations
- ItalyUnited StatesChina
In The Last Decade
Vincenzo Piuri
361 papers receiving 5.5k citations
Peers
Comparison fields: 5 of 173
- Computer Vision and Pattern Recognition 1.9k
- Artificial Intelligence 1.7k
- Signal Processing 1.2k
- Information Systems 988
- Electrical and Electronic Engineering 968
Countries citing papers authored by Vincenzo Piuri
This map shows the geographic impact of Vincenzo Piuri'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 Vincenzo Piuri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vincenzo Piuri more than expected).
Fields of papers citing papers by Vincenzo Piuri
This network shows the impact of papers produced by Vincenzo Piuri. 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 Vincenzo Piuri. The network helps show where Vincenzo Piuri may publish in the future.
Co-authorship network of co-authors of Vincenzo Piuri
This figure shows the co-authorship network connecting the top 25 collaborators of Vincenzo Piuri. A scholar is included among the top collaborators of Vincenzo Piuri 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 Vincenzo Piuri. Vincenzo Piuri 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 | 4 | |
| 4 | 2 | |
| 5 | 3 | |
| 6 | 3 | |
| 7 | 3 | |
| 8 | 2 | |
| 9 | 6 | |
| 10 | 29 | |
| 11 | 20 | |
| 12 | 18 | |
| 13 | 11 | |
| 14 | 10 | |
| 15 | 26 | |
| 16 | 257 | |
| 17 | 9 | |
| 18 | 23 | |
| 19 | 1 | |
| 20 | 7 |
About Vincenzo Piuri
Vincenzo Piuri is a scholar working on Hardware and Architecture, Signal Processing and Computer Vision and Pattern Recognition, having authored 399 papers that have together received 5.9k indexed citations. Recurring topics across this work include Biometric Identification and Security (47 papers), Neural Networks and Applications (38 papers) and VLSI and Analog Circuit Testing (31 papers). The work is most often cited by research in Signal Processing (1.2k citations), Computer Vision and Pattern Recognition (1.9k citations) and Hardware and Architecture (454 citations). Vincenzo Piuri has collaborated with scholars based in Italy, United States and China. Frequent co-authors include Fabio Scotti, Ruggero Donida Labati, Angelo Genovese, Cesare Alippi, Ravi Jhawar, Enrique Muñoz, Alessandro Ferrero, Luca Breveglieri, Stefano Ferrari and Roberto Sassi. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Signal Processing and IEEE Access.
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.