Jacopo Cavazza
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Cognitive Neuroscience
- Social Psychology
- Biomedical Engineering
- Co-authors
- Vittorio MurinoRiccardo VolpiPietro MorerioRenè VidalFrancesco BossiCesco WillemseSerena MarchesiAgnieszka Wykowska
- Topics
- Domain Adaptation and Few-Shot Learning (7 papers)Multimodal Machine Learning Applications (3 papers)Human Pose and Action Recognition (3 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceScientific ReportsInternational Journal of Computer Vision
- Partner nations
- ItalyUnited StatesSweden
In The Last Decade
Jacopo Cavazza
14 papers receiving 139 citations
Peers
Comparison fields: 5 of 50
- Artificial Intelligence 64
- Computer Vision and Pattern Recognition 56
- Cognitive Neuroscience 37
- Social Psychology 33
- Biomedical Engineering 12
Countries citing papers authored by Jacopo Cavazza
This map shows the geographic impact of Jacopo Cavazza'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 Jacopo Cavazza with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jacopo Cavazza more than expected).
Fields of papers citing papers by Jacopo Cavazza
This network shows the impact of papers produced by Jacopo Cavazza. 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 Jacopo Cavazza. The network helps show where Jacopo Cavazza may publish in the future.
Co-authorship network of co-authors of Jacopo Cavazza
This figure shows the co-authorship network connecting the top 25 collaborators of Jacopo Cavazza. A scholar is included among the top collaborators of Jacopo Cavazza 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 Jacopo Cavazza. Jacopo Cavazza 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 | 9 | |
| 3 | 2 | |
| 4 | 5 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 0 | |
| 8 | 45 | |
| 9 | 3 | |
| 10 | 8 | |
| 11 | Visually-Driven Semantic Augmentation for Zero-Shot Learning. | 2 |
| 12 | Dropout as a Low-Rank Regularizer for Matrix Factorization. | 3 |
| 13 | Curriculum Dropout | 10 |
| 14 | 38 | |
| 15 | 8 |
About Jacopo Cavazza
Jacopo Cavazza is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 15 papers that have together received 139 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (7 papers), Multimodal Machine Learning Applications (3 papers) and Human Pose and Action Recognition (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (56 citations), Artificial Intelligence (64 citations) and Cognitive Neuroscience (37 citations). Jacopo Cavazza has collaborated with scholars based in Italy, United States and Sweden. Frequent co-authors include Vittorio Murino, Riccardo Volpi, Pietro Morerio, Renè Vidal, Francesco Bossi, Cesco Willemse, Serena Marchesi, Agnieszka Wykowska, Alessio Del Bue and Cristina Becchio. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and International Journal of Computer Vision.
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.