Nicola Capece
- Computer Vision and Pattern Recognition top 5%
- Human-Computer Interaction top 5%
- Artificial Intelligence
- Information Systems
- Cognitive Neuroscience
- Co-authors
- Ugo ErraDomenica MiraudaGiuseppe ScannielloMichele LanzaSimone RomanoPaola D’AntonioFrancesco ToscanoΜάριος Δρόσος
- Topics
- Video Surveillance and Tracking Methods (6 papers)Virtual Reality Applications and Impacts (5 papers)Hand Gesture Recognition Systems (5 papers)
- Cited by
- Human-Computer InteractionComputer Vision and Pattern RecognitionComputer Graphics and Computer-Aided Design
- Partner nations
- ItalySwitzerlandSweden
In The Last Decade
Nicola Capece
33 papers receiving 316 citations
Peers
Comparison fields: 5 of 75
- Computer Vision and Pattern Recognition 162
- Human-Computer Interaction 108
- Artificial Intelligence 38
- Information Systems 33
- Cognitive Neuroscience 23
Countries citing papers authored by Nicola Capece
This map shows the geographic impact of Nicola Capece'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 Nicola Capece with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicola Capece more than expected).
Fields of papers citing papers by Nicola Capece
This network shows the impact of papers produced by Nicola Capece. 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 Nicola Capece. The network helps show where Nicola Capece may publish in the future.
Co-authorship network of co-authors of Nicola Capece
This figure shows the co-authorship network connecting the top 25 collaborators of Nicola Capece. A scholar is included among the top collaborators of Nicola Capece 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 Nicola Capece. Nicola Capece 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 | 0 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 12 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 25 | |
| 12 | 31 | |
| 13 | 2 | |
| 14 | 5 | |
| 15 | 17 | |
| 16 | 17 | |
| 17 | 8 | |
| 18 | 31 | |
| 19 | 13 | |
| 20 | 5 |
About Nicola Capece
Nicola Capece is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Geology, having authored 36 papers that have together received 325 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (6 papers), Virtual Reality Applications and Impacts (5 papers) and Hand Gesture Recognition Systems (5 papers). The work is most often cited by research in Human-Computer Interaction (108 citations), Computer Vision and Pattern Recognition (162 citations) and Computer Graphics and Computer-Aided Design (13 citations). Nicola Capece has collaborated with scholars based in Italy, Switzerland and Sweden. Frequent co-authors include Ugo Erra, Domenica Mirauda, Giuseppe Scanniello, Michele Lanza, Simone Romano, Paola D’Antonio, Francesco Toscano, Μάριος Δρόσος, Luigi Gallo and Giuseppe Caggianese. Their work appears in journals such as IEEE Access, Sustainability and Applied Sciences.
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.