Raffaella Lanzarotti
- Computer Vision and Pattern Recognition top 5%
- Biomedical Engineering
- Cardiology and Cardiovascular Medicine
- Signal Processing top 5%
- Human-Computer Interaction top 5%
- Co-authors
- Paola CampadelliGiuliano GrossiGiuseppe BoccignoneAlessandro D’AmelioJianyi LinVittorio CuculoDonatello ConteNicoletta Noceti
- Topics
- Face recognition and analysis (20 papers)Face and Expression Recognition (19 papers)Biometric Identification and Security (7 papers)
- Journals
- PLoS ONEIEEE AccessSensors
- Partner nations
- ItalyFranceUnited Arab Emirates
In The Last Decade
Raffaella Lanzarotti
40 papers receiving 583 citations
Peers
Comparison fields: 5 of 84
- Computer Vision and Pattern Recognition 302
- Biomedical Engineering 153
- Cardiology and Cardiovascular Medicine 114
- Signal Processing 104
- Human-Computer Interaction 95
Countries citing papers authored by Raffaella Lanzarotti
This map shows the geographic impact of Raffaella Lanzarotti'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 Raffaella Lanzarotti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raffaella Lanzarotti more than expected).
Fields of papers citing papers by Raffaella Lanzarotti
This network shows the impact of papers produced by Raffaella Lanzarotti. 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 Raffaella Lanzarotti. The network helps show where Raffaella Lanzarotti may publish in the future.
Co-authorship network of co-authors of Raffaella Lanzarotti
This figure shows the co-authorship network connecting the top 25 collaborators of Raffaella Lanzarotti. A scholar is included among the top collaborators of Raffaella Lanzarotti 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 Raffaella Lanzarotti. Raffaella Lanzarotti 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 | 2 | |
| 4 | 13 | |
| 5 | 3 | |
| 6 | 15 | |
| 7 | 6 | |
| 8 | 19 | |
| 9 | 9 | |
| 10 | 3 | |
| 11 | 11 | |
| 12 | 16 | |
| 13 | 4 | |
| 14 | 28 | |
| 15 | 7 | |
| 16 | Eye localization: a survey | 17 |
| 17 | 6 | |
| 18 | 5 | |
| 19 | 27 | |
| 20 | 6 |
About Raffaella Lanzarotti
Raffaella Lanzarotti is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Neuropsychology and Physiological Psychology, having authored 42 papers that have together received 602 indexed citations. Recurring topics across this work include Face recognition and analysis (20 papers), Face and Expression Recognition (19 papers) and Biometric Identification and Security (7 papers). The work is most often cited by research in Human-Computer Interaction (95 citations), Computer Vision and Pattern Recognition (302 citations) and Signal Processing (104 citations). Raffaella Lanzarotti has collaborated with scholars based in Italy, France and United Arab Emirates. Frequent co-authors include Paola Campadelli, Giuliano Grossi, Giuseppe Boccignone, Alessandro D’Amelio, Jianyi Lin, Vittorio Cuculo, Donatello Conte, Nicoletta Noceti, Francesca Odone and Paolo Napoletano. Their work appears in journals such as PLoS ONE, 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.