Marco Toldo
Impact in
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- Multimodal Machine Learning Applications
- Advanced Neural Network Applications
- Video Surveillance and Tracking Methods
- Advanced Image and Video Retrieval Techniques
- Artificial Intelligence top 5%
- Domain Adaptation and Few-Shot Learning
- Privacy-Preserving Technologies in Data
- Machine Learning and ELM
Papers in
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- Domain Adaptation and Few-Shot Learning 9
- Machine Learning and ELM 2
- Privacy-Preserving Technologies in Data 2
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- Multimodal Machine Learning Applications 6
- Advanced Neural Network Applications 3
- Co-authors
- Pietro Zanuttigh (9 shared papers)Umberto Michieli (9 shared papers)Mete Özay (2 shared papers)Gianluca Agresti (1 shared paper)Alberto Rigon (1 shared paper)Barbara Caputo (1 shared paper)Marco Ciccone (1 shared paper)Luke M. Mosley (1 shared paper)
- Journals
- Chemosphere (1 paper)The Visual Computer (1 paper)Image and Vision Computing (1 paper)IEEE Internet of Things Journal (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)
- Partner nations
- ItalyAustraliaSouth Korea
In The Last Decade
Marco Toldo
12 papers receiving 372 citations
Peers
Comparison fields: 5 of 65
- Computer Vision and Pattern Recognition 239
- Artificial Intelligence 252
- Radiology, Nuclear Medicine and Imaging 64
- Media Technology 17
- Geology 10
Countries citing papers authored by Marco Toldo
This map shows the geographic impact of Marco Toldo'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 Marco Toldo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco Toldo more than expected).
Fields of papers citing papers by Marco Toldo
This network shows the impact of papers produced by Marco Toldo. 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 Marco Toldo. The network helps show where Marco Toldo may publish in the future.
Co-authors
The 11 scholars most cited alongside Marco Toldo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 119 | |
| 2 | 2021 | 77 | |
| 3 | 2021 | 39 | |
| 4 | 2020 | 31 | |
| 5 | 2022 | 26 | |
| 6 | 2023 | 23 | |
| 7 | 2023 | 23 | |
| 8 | 2019 | 12 | |
| 9 | 2020 | 11 | |
| 10 | 2022 | 7 | |
| 11 | 2024 | 5 | |
| 12 | 2023 | 2 |
About Marco Toldo
Marco Toldo is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Oceanography and Environmental Chemistry, having authored 12 papers that have together received 375 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (9 papers), COVID-19 diagnosis using AI (6 papers), Multimodal Machine Learning Applications (6 papers), Advanced Neural Network Applications (3 papers), Machine Learning and ELM (2 papers), Privacy-Preserving Technologies in Data (2 papers), Soil and Water Nutrient Dynamics (1 paper) and Water Quality and Pollution Assessment (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (239 citations), Artificial Intelligence (252 citations), Radiology, Nuclear Medicine and Imaging (64 citations), Media Technology (17 citations) and Geology (10 citations). Marco Toldo has collaborated with scholars based in Italy, Australia and South Korea. Frequent co-authors include Pietro Zanuttigh, Umberto Michieli, Mete Özay, Gianluca Agresti, Alberto Rigon, Barbara Caputo, Marco Ciccone, Luke M. Mosley, Marco Minella and Luca Carena. Their work appears in journals such as Chemosphere, The Visual Computer, Image and Vision Computing, IEEE Internet of Things Journal and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.