Matteo Matteucci
- Computer Vision and Pattern Recognition top 1%
- Cognitive Neuroscience top 2%
- Artificial Intelligence top 2%
- Biomedical Engineering top 5%
- Aerospace Engineering top 2%
- Co-authors
- Sara ComaiAnna Maria BianchiS. CeruttiMarco CanniciAndrea BonariniAva ValiChiara PlizzariMartín O. Méndez
- Topics
- Robotics and Sensor-Based Localization (32 papers)Autonomous Vehicle Technology and Safety (17 papers)Robotic Path Planning Algorithms (17 papers)
- Journals
- SHILAP Revista de lepidopterologíaBioinformaticsPLoS ONE
- Partner nations
- ItalyGermanySwitzerland
In The Last Decade
Matteo Matteucci
234 papers receiving 3.9k citations
Hit Papers
Peers
Comparison fields: 5 of 172
- Computer Vision and Pattern Recognition 1.0k
- Cognitive Neuroscience 798
- Artificial Intelligence 722
- Biomedical Engineering 644
- Aerospace Engineering 470
Countries citing papers authored by Matteo Matteucci
This map shows the geographic impact of Matteo Matteucci'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 Matteo Matteucci with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matteo Matteucci more than expected).
Fields of papers citing papers by Matteo Matteucci
This network shows the impact of papers produced by Matteo Matteucci. 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 Matteo Matteucci. The network helps show where Matteo Matteucci may publish in the future.
Co-authorship network of co-authors of Matteo Matteucci
This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Matteucci. A scholar is included among the top collaborators of Matteo Matteucci 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 Matteo Matteucci. Matteo Matteucci 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 | 2 | |
| 4 | 7 | |
| 5 | 0 | |
| 6 | 5 | |
| 7 | 2 | |
| 8 | 3 | |
| 9 | 8 | |
| 10 | 5 | |
| 11 | 5 | |
| 12 | 16 | |
| 13 | 74 | |
| 14 | 15 | |
| 15 | 4 | |
| 16 | 8 | |
| 17 | 8 | |
| 18 | Brain Control of a Smart Wheelchair | 17 |
| 19 | EVOLUTIONARY LEARNING OF RICH NEURAL NETWORKS IN THE BAYESIAN MODEL SELECTION FRAMEWORK | 5 |
| 20 | A novel model to rule behavior interaction | 3 |
About Matteo Matteucci
Matteo Matteucci is a scholar working on Computer Vision and Pattern Recognition, Human Factors and Ergonomics and Software, having authored 246 papers that have together received 4.0k indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (32 papers), Autonomous Vehicle Technology and Safety (17 papers) and Robotic Path Planning Algorithms (17 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.0k citations), Human-Computer Interaction (246 citations) and Cognitive Neuroscience (798 citations). Matteo Matteucci has collaborated with scholars based in Italy, Germany and Switzerland. Frequent co-authors include Sara Comai, Anna Maria Bianchi, S. Cerutti, Marco Cannici, Andrea Bonarini, Ava Vali, Chiara Plizzari, Martín O. Méndez, Luca Mainardi and Andréa Zanchi. Their work appears in journals such as SHILAP Revista de lepidopterología, Bioinformatics and PLoS ONE.
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.