Giovanni Paragliola
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications top 10%
- Cognitive Neuroscience
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Antonio CoronatoMuddasar NaeemGiuseppe De PietroPatrizia RibinoClaudia Di NapoliZaib UllahMykola PechenizkiySajid Bashir
- Topics
- Machine Learning in Healthcare (10 papers)Context-Aware Activity Recognition Systems (7 papers)Privacy-Preserving Technologies in Data (6 papers)
In The Last Decade
Giovanni Paragliola
33 papers receiving 491 citations
Peers
Comparison fields: 5 of 101
- Artificial Intelligence 238
- Computer Vision and Pattern Recognition 67
- Computer Networks and Communications 66
- Cognitive Neuroscience 65
- Radiology, Nuclear Medicine and Imaging 60
Countries citing papers authored by Giovanni Paragliola
This map shows the geographic impact of Giovanni Paragliola'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 Giovanni Paragliola with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Giovanni Paragliola more than expected).
Fields of papers citing papers by Giovanni Paragliola
This network shows the impact of papers produced by Giovanni Paragliola. 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 Giovanni Paragliola. The network helps show where Giovanni Paragliola may publish in the future.
Co-authorship network of co-authors of Giovanni Paragliola
This figure shows the co-authorship network connecting the top 25 collaborators of Giovanni Paragliola. A scholar is included among the top collaborators of Giovanni Paragliola 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 Giovanni Paragliola. Giovanni Paragliola is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 6 | |
| 5 | 6 | |
| 6 | 2 | |
| 7 | 5 | |
| 8 | 8 | |
| 9 | 3 | |
| 10 | 4 | |
| 11 | 35 | |
| 12 | 7 | |
| 13 | 2 | |
| 14 | 182 | |
| 15 | 25 | |
| 16 | 12 | |
| 17 | A Reinforcement-Learning-Based Approach for the Planning of Safety Strategies in AAL Applications. | 1 |
| 18 | 14 | |
| 19 | 42 | |
| 20 | 6 |
About Giovanni Paragliola
Giovanni Paragliola is a scholar working on Software, Health Informatics and Artificial Intelligence, having authored 35 papers that have together received 520 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (10 papers), Context-Aware Activity Recognition Systems (7 papers) and Privacy-Preserving Technologies in Data (6 papers). The work is most often cited by research in Health Informatics (51 citations), Health Information Management (49 citations) and Artificial Intelligence (238 citations). Giovanni Paragliola has collaborated with scholars based in Italy, Germany and Canada. Frequent co-authors include Antonio Coronato, Muddasar Naeem, Giuseppe De Pietro, Patrizia Ribino, Claudia Di Napoli, Zaib Ullah, Mykola Pechenizkiy, Sajid Bashir, Rustam Stolkin and Carmelo Mineo. Their work appears in journals such as Expert Systems with Applications, 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.