Fabio Cuzzolin

2.7k citations
78 papers · 1.1k · h-index 17

Impact in

Papers in

Fabio Cuzzolin

66 papers receiving 1.1k citations

Peers

Fabio Cuzzolin
Comparison fields: 5 of 103
  • Management Science and Operations Research 299
  • Computer Vision and Pattern Recognition 408
  • Artificial Intelligence 580
  • Safety, Risk, Reliability and Quality 116
  • Statistics and Probability 80
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Junhai Zhai China
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Citations per field
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Citations per year

Countries citing papers authored by Fabio Cuzzolin

Since Specialization
Citations

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

Fields of papers citing papers by Fabio Cuzzolin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Fabio Cuzzolin, 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 Fabio Cuzzolin Line = papers co-authored together Fabio Cuzzolin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 78 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019187
2 2021102
3 200890
4 202269
5 202150
6 201740
7 201339
8 201439
9 202135
10 202234
11 200729
12 201227
13 200425
14 201724
15 201224
16 200624
17 202122
18 201915
19 202213
20 202013

About Fabio Cuzzolin

Fabio Cuzzolin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Management Science and Operations Research, Computational Theory and Mathematics and Statistics and Probability, having authored 78 papers that have together received 1.1k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (22 papers), Human Pose and Action Recognition (20 papers), Multi-Criteria Decision Making (16 papers), Anomaly Detection Techniques and Applications (14 papers), Video Surveillance and Tracking Methods (14 papers), Rough Sets and Fuzzy Logic (10 papers), Fuzzy Systems and Optimization (7 papers) and Multimodal Machine Learning Applications (6 papers). The work is most often cited by research in Management Science and Operations Research (299 citations), Computer Vision and Pattern Recognition (408 citations), Artificial Intelligence (580 citations), Safety, Risk, Reliability and Quality (116 citations) and Statistics and Probability (80 citations). Fabio Cuzzolin has collaborated with scholars based in United Kingdom, Italy and United States. Frequent co-authors include Yu Liu, Zhunga Liu, Jean Dezert, Michael Sapienza, Philip H. S. Torr, Victor Hugo C. de Albuquerque, Salman Khan, Barbara J. Sahakian, Suman Saha and Gurkirt Singh. Their work appears in journals such as IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics), International Journal of Approximate Reasoning, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Pattern Analysis and Machine Intelligence and Information Fusion.

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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