Fabio Cermelli

43 total papers · 628 total citations
14 papers, 316 citations indexed

About

Fabio Cermelli is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Fabio Cermelli has authored 14 papers receiving a total of 316 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 1 paper in Computer Networks and Communications. Recurrent topics in Fabio Cermelli's work include Advanced Neural Network Applications (9 papers), Domain Adaptation and Few-Shot Learning (7 papers) and Multimodal Machine Learning Applications (6 papers). Fabio Cermelli is often cited by papers focused on Advanced Neural Network Applications (9 papers), Domain Adaptation and Few-Shot Learning (7 papers) and Multimodal Machine Learning Applications (6 papers). Fabio Cermelli collaborates with scholars based in Italy, Germany and France. Fabio Cermelli's co-authors include Massimiliano Mancini, Samuel Rota Bulò, Barbara Caputo, Marco Ciccone, Carlo Masone, Matthieu Cord, Arthur Douillard, Giuseppe Averta, Yongqin Xian and Fabrizio Lamberti and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Robotics and Automation Letters and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Fabio Cermelli

12 papers receiving 314 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Fabio Cermelli	234	220	51	22	15	14	316
Yuang Liu	226 1.0×	238 1.1×	50 1.0×	16 0.7×	10 0.7×	8	348
Marco Toldo	247 1.1×	232 1.1×	65 1.3×	17 0.8×	17 1.1×	12	365
Jiequan Cui	244 1.0×	170 0.8×	48 0.9×	21 1.0×	12 0.8×	8	341
Qing Xu	136 0.6×	154 0.7×	80 1.6×	19 0.9×	13 0.9×	22	286
Ruijia Xu	224 1.0×	175 0.8×	23 0.5×	22 1.0×	20 1.3×	9	348
Debasmit Das	166 0.7×	133 0.6×	27 0.5×	14 0.6×	24 1.6×	19	299
Harish G. Ramaswamy	230 1.0×	129 0.6×	31 0.6×	15 0.7×	9 0.6×	14	315
Hossein Kashiani	139 0.6×	172 0.8×	100 2.0×	25 1.1×	9 0.6×	15	330
Riaz Ali	108 0.5×	134 0.6×	83 1.6×	27 1.2×	23 1.5×	20	300
Gianluca Agresti	88 0.4×	187 0.8×	24 0.5×	20 0.9×	11 0.7×	14	245

Countries citing papers authored by Fabio Cermelli

Since Specialization

Citations

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

Fields of papers citing papers by Fabio Cermelli

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fabio Cermelli

This figure shows the co-authorship network connecting the top 25 collaborators of Fabio Cermelli. A scholar is included among the top collaborators of Fabio Cermelli 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 Fabio Cermelli. Fabio Cermelli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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