Giuliano Grossi
- Biomedical Engineering
- Computer Vision and Pattern Recognition top 10%
- Cardiology and Cardiovascular Medicine
- Artificial Intelligence
- Signal Processing top 10%
- Co-authors
- Raffaella LanzarottiJianyi LinVittorio CuculoGiuseppe BoccignoneAlessandro D’AmelioDonatello ConteFrancesca OdoneNicoletta Noceti
- Topics
- Sparse and Compressive Sensing Techniques (8 papers)Face recognition and analysis (7 papers)ECG Monitoring and Analysis (6 papers)
- Cited by
- Signal ProcessingComputer Vision and Pattern RecognitionCardiology and Cardiovascular Medicine
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
- Partner nations
- ItalyFranceUnited States
In The Last Decade
Giuliano Grossi
47 papers receiving 452 citations
Peers
Comparison fields: 5 of 84
- Biomedical Engineering 147
- Computer Vision and Pattern Recognition 122
- Cardiology and Cardiovascular Medicine 117
- Artificial Intelligence 74
- Signal Processing 70
Countries citing papers authored by Giuliano Grossi
This map shows the geographic impact of Giuliano Grossi'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 Giuliano Grossi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Giuliano Grossi more than expected).
Fields of papers citing papers by Giuliano Grossi
This network shows the impact of papers produced by Giuliano Grossi. 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 Giuliano Grossi. The network helps show where Giuliano Grossi may publish in the future.
Co-authorship network of co-authors of Giuliano Grossi
This figure shows the co-authorship network connecting the top 25 collaborators of Giuliano Grossi. A scholar is included among the top collaborators of Giuliano Grossi 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 Giuliano Grossi. Giuliano Grossi 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 | 12 | |
| 4 | 13 | |
| 5 | 3 | |
| 6 | 9 | |
| 7 | 7 | |
| 8 | 19 | |
| 9 | 6 | |
| 10 | 1 | |
| 11 | 5 | |
| 12 | Adaptation and validation of the "Continuing Bond Scale" in an Italian context. An instrument for studying the persistence of the bond with the deceased in normal and abnormal grief | 2 |
| 13 | 9 | |
| 14 | 3 | |
| 15 | 12 | |
| 16 | 11 | |
| 17 | 16 | |
| 18 | Hub-betweenness analysis in delay tolerant networks inferred by real traces | 0 |
| 19 | Analysis of a Genetic Model. | 3 |
| 20 | Fast Prototyping for Hardware Neural Networks | 2 |
About Giuliano Grossi
Giuliano Grossi is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Neuropsychology and Physiological Psychology, having authored 49 papers that have together received 461 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (8 papers), Face recognition and analysis (7 papers) and ECG Monitoring and Analysis (6 papers). The work is most often cited by research in Signal Processing (70 citations), Computer Vision and Pattern Recognition (122 citations) and Cardiology and Cardiovascular Medicine (117 citations). Giuliano Grossi has collaborated with scholars based in Italy, France and United States. Frequent co-authors include Raffaella Lanzarotti, Jianyi Lin, Vittorio Cuculo, Giuseppe Boccignone, Alessandro D’Amelio, Donatello Conte, Francesca Odone, Nicoletta Noceti, Paolo Napoletano and Federico Pedersini. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.
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.