Francesco Pascale
- Artificial Intelligence top 5%
- Computer Networks and Communications top 5%
- Information Systems top 5%
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Marco LombardiDomenico SantanielloFrancesco ColaceMassimo De SantoSaverio LemmaAntonio PietrosantoFabio ClariziaMario Casillo
- Topics
- Context-Aware Activity Recognition Systems (7 papers)Sentiment Analysis and Opinion Mining (6 papers)Vehicular Ad Hoc Networks (VANETs) (6 papers)
- Partner nations
- ItalyUnited KingdomEcuador
In The Last Decade
Francesco Pascale
32 papers receiving 607 citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Artificial Intelligence 256
- Computer Networks and Communications 206
- Information Systems 143
- Electrical and Electronic Engineering 123
- Computer Vision and Pattern Recognition 87
Countries citing papers authored by Francesco Pascale
This map shows the geographic impact of Francesco Pascale'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 Francesco Pascale with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Francesco Pascale more than expected).
Fields of papers citing papers by Francesco Pascale
This network shows the impact of papers produced by Francesco Pascale. 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 Francesco Pascale. The network helps show where Francesco Pascale may publish in the future.
Co-authorship network of co-authors of Francesco Pascale
This figure shows the co-authorship network connecting the top 25 collaborators of Francesco Pascale. A scholar is included among the top collaborators of Francesco Pascale 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 Francesco Pascale. Francesco Pascale is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 3 | |
| 3 | 2 | |
| 4 | Internet of Things: A General Overview between Architectures, Protocols and Applicationsbreakdown → | 167 |
| 5 | 11 | |
| 6 | 47 | |
| 7 | 19 | |
| 8 | 21 | |
| 9 | 18 | |
| 10 | 25 | |
| 11 | 5 | |
| 12 | 1 | |
| 13 | 28 | |
| 14 | 5 | |
| 15 | 104 | |
| 16 | 8 | |
| 17 | 8 | |
| 18 | 12 | |
| 19 | 1 | |
| 20 | 1 |
About Francesco Pascale
Francesco Pascale is a scholar working on Signal Processing, Computer Science Applications and Artificial Intelligence, having authored 33 papers that have together received 636 indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (7 papers), Sentiment Analysis and Opinion Mining (6 papers) and Vehicular Ad Hoc Networks (VANETs) (6 papers). The work is most often cited by research in Computer Science Applications (59 citations), Computer Networks and Communications (206 citations) and Signal Processing (87 citations). Francesco Pascale has collaborated with scholars based in Italy, United Kingdom and Ecuador. Frequent co-authors include Marco Lombardi, Domenico Santaniello, Francesco Colace, Massimo De Santo, Saverio Lemma, Antonio Pietrosanto, Fabio Clarizia, Mario Casillo, Fabio Mercorio and Mario Mezzanzanica. Their work appears in journals such as Pattern Recognition Letters, Applied Sciences and Electronics.
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.