Fabrizio Lamberti

197 papers receiving 2.7k citations

Fabrizio Lamberti's Hit Papers

Data augmentation for medical imaging: A systematic literature review 2022 · 195 citations
1950+2+5Years since publication100200300

Peers

Fabrizio Lamberti
Comparison fields: 5 of 161
  • Human-Computer Interaction 657
  • Computer Vision and Pattern Recognition 968
  • Computer Graphics and Computer-Aided Design 157
  • Information Systems 733
  • Hardware and Architecture 128
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Countries citing papers authored by Fabrizio Lamberti

Since Specialization
Citations

This map shows the geographic impact of Fabrizio Lamberti'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 Fabrizio Lamberti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabrizio Lamberti more than expected).

Fields of papers citing papers by Fabrizio Lamberti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fabrizio Lamberti. 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 Fabrizio Lamberti. The network helps show where Fabrizio Lamberti may publish in the future.

Co-authors

The 25 scholars most cited alongside Fabrizio Lamberti, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Fabrizio Lamberti Line = papers co-authored together Fabrizio Lamberti links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 219 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Blockchain and Smart Contracts for Insurance: Is the Technology Mature Enough?
Hit paper breakdown →
2018316
2
Data augmentation for medical imaging: A systematic literature review
Hit paper breakdown →
2022195
3 2018167
4 2007104
5 201377
6 200876
7 201476
8 201951
9 200648
10 201546
11 201544
12 201843
13 202041
14 202138
15 201137
16 202237
17 202136
18 202135
19 201033
20 200332

About Fabrizio Lamberti

Fabrizio Lamberti is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction, Artificial Intelligence, Cognitive Neuroscience and Information Systems, having authored 219 papers that have together received 2.9k indexed citations. Recurring topics across this work include Virtual Reality Applications and Impacts (48 papers), Augmented Reality Applications (39 papers), Interactive and Immersive Displays (21 papers), Tactile and Sensory Interactions (20 papers), Advanced Vision and Imaging (17 papers), Teleoperation and Haptic Systems (16 papers), Human Motion and Animation (16 papers) and Cloud Computing and Remote Desktop Technologies (12 papers). The work is most often cited by research in Human-Computer Interaction (657 citations), Computer Vision and Pattern Recognition (968 citations), Computer Graphics and Computer-Aided Design (157 citations), Information Systems (733 citations) and Hardware and Architecture (128 citations). Fabrizio Lamberti has collaborated with scholars based in Italy, Spain and Canada. Frequent co-authors include Andrea Sanna, Claudio Giovanni Demartini, Valentina Gatteschi, Gianluca Paravati, Lia Morra, Alberto Cannavò, Filippo Gabriele Pratticò, Paolo Montuschi, Davide Calandra and Federico Manuri. Their work appears in journals such as IEEE Consumer Electronics Magazine, IEEE Transactions on Consumer Electronics, IT Professional, IEEE Transactions on Visualization and Computer Graphics and IEEE Transactions on Learning Technologies.

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.

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