Laura Papaleo
- Computer Vision and Pattern Recognition top 10%
- Computational Theory and Mathematics top 5%
- Computational Mechanics
- Computer Graphics and Computer-Aided Design top 5%
- Aerospace Engineering
- Co-authors
- Leila De FlorianiMichela SpagnuoloDaniela GiorgiClaudia LandiSilvia BiasottiBianca FalcidienoPatrizio FrosiniAndrea Fusiello
- Topics
- Computer Graphics and Visualization Techniques (7 papers)3D Shape Modeling and Analysis (7 papers)Semantic Web and Ontologies (4 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionComputational Theory and Mathematics
- Partner nations
- ItalyAustraliaUnited States
In The Last Decade
Laura Papaleo
22 papers receiving 230 citations
Peers
Comparison fields: 5 of 53
- Computer Vision and Pattern Recognition 134
- Computational Theory and Mathematics 87
- Computational Mechanics 59
- Computer Graphics and Computer-Aided Design 49
- Aerospace Engineering 29
Countries citing papers authored by Laura Papaleo
This map shows the geographic impact of Laura Papaleo'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 Laura Papaleo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Laura Papaleo more than expected).
Fields of papers citing papers by Laura Papaleo
This network shows the impact of papers produced by Laura Papaleo. 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 Laura Papaleo. The network helps show where Laura Papaleo may publish in the future.
Co-authorship network of co-authors of Laura Papaleo
This figure shows the co-authorship network connecting the top 25 collaborators of Laura Papaleo. A scholar is included among the top collaborators of Laura Papaleo 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 Laura Papaleo. Laura Papaleo 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 | Semantic Web and Declarative Agent Languages and Technologies: Current and Future Trends (Position Paper) | 1 |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 2 | |
| 6 | 10 | |
| 7 | 3 | |
| 8 | 3 | |
| 9 | 2 | |
| 10 | 14 | |
| 11 | Integrating agents and virtual institutions for sharing cultural heritage on the Web | 3 |
| 12 | 131 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 10 | |
| 16 | 1 | |
| 17 | 1 | |
| 18 | 9 | |
| 19 | 18 | |
| 20 | 11 |
About Laura Papaleo
Laura Papaleo is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Geology, having authored 24 papers that have together received 244 indexed citations. Recurring topics across this work include Computer Graphics and Visualization Techniques (7 papers), 3D Shape Modeling and Analysis (7 papers) and Semantic Web and Ontologies (4 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (49 citations), Computer Vision and Pattern Recognition (134 citations) and Computational Theory and Mathematics (87 citations). Laura Papaleo has collaborated with scholars based in Italy, Australia and United States. Frequent co-authors include Leila De Floriani, Michela Spagnuolo, Daniela Giorgi, Claudia Landi, Silvia Biasotti, Bianca Falcidieno, Patrizio Frosini, Andrea Fusiello, Enrico Puppo and Gabriella Dodero. Their work appears in journals such as ACM Computing Surveys, Signal Processing Image Communication and Mammalian Biology.
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.