Luca Mussi
- Artificial Intelligence top 10%
- Computational Theory and Mathematics top 10%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications
- Aerospace Engineering
- Co-authors
- Stefano CagnoniFabio DaolioYoussef S. G. NashedPablo MesejoPier Paolo PortaMonica MordoniniPaolo MediciElena Cardarelli
- Topics
- Metaheuristic Optimization Algorithms Research (5 papers)Evolutionary Algorithms and Applications (3 papers)Advanced Image and Video Retrieval Techniques (3 papers)
- Cited by
- Artificial IntelligenceComputational Theory and MathematicsComputer Vision and Pattern Recognition
- Journals
- SHILAP Revista de lepidopterologíaInformation SciencesApplied Soft Computing
- Partner nations
- ItalySwitzerlandUnited Kingdom
In The Last Decade
Luca Mussi
13 papers receiving 247 citations
Peers
Comparison fields: 5 of 69
- Artificial Intelligence 164
- Computational Theory and Mathematics 67
- Computer Vision and Pattern Recognition 63
- Computer Networks and Communications 28
- Aerospace Engineering 22
Countries citing papers authored by Luca Mussi
This map shows the geographic impact of Luca Mussi'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 Luca Mussi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luca Mussi more than expected).
Fields of papers citing papers by Luca Mussi
This network shows the impact of papers produced by Luca Mussi. 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 Luca Mussi. The network helps show where Luca Mussi may publish in the future.
Co-authorship network of co-authors of Luca Mussi
This figure shows the co-authorship network connecting the top 25 collaborators of Luca Mussi. A scholar is included among the top collaborators of Luca Mussi 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 Luca Mussi. Luca Mussi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 4 | |
| 3 | 4 | |
| 4 | 1 | |
| 5 | 4 | |
| 6 | 44 | |
| 7 | 4 | |
| 8 | 31 | |
| 9 | 11 | |
| 10 | 122 | |
| 11 | 5 | |
| 12 | 29 | |
| 13 | 7 |
About Luca Mussi
Luca Mussi is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Industrial and Manufacturing Engineering, having authored 13 papers that have together received 272 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (5 papers), Evolutionary Algorithms and Applications (3 papers) and Advanced Image and Video Retrieval Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (164 citations), Computational Theory and Mathematics (67 citations) and Computer Vision and Pattern Recognition (63 citations). Luca Mussi has collaborated with scholars based in Italy, Switzerland and United Kingdom. Frequent co-authors include Stefano Cagnoni, Fabio Daolio, Youssef S. G. Nashed, Pablo Mesejo, Pier Paolo Porta, Monica Mordonini, Paolo Medici, Elena Cardarelli, Giovanni Adorni and Saeid Sanei. Their work appears in journals such as SHILAP Revista de lepidopterología, Information Sciences and Applied Soft Computing.
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.