Marcello Salmeri

36 papers and 435 indexed citations i.

About

Marcello Salmeri is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Marcello Salmeri has authored 36 papers receiving a total of 435 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 14 papers in Computer Vision and Pattern Recognition and 7 papers in Electrical and Electronic Engineering. Recurrent topics in Marcello Salmeri’s work include AI in cancer detection (17 papers), Image and Signal Denoising Methods (6 papers) and Neural Networks and Applications (5 papers). Marcello Salmeri is often cited by papers focused on AI in cancer detection (17 papers), Image and Signal Denoising Methods (6 papers) and Neural Networks and Applications (5 papers). Marcello Salmeri collaborates with scholars based in Italy, Canada and Norway. Marcello Salmeri's co-authors include Arianna Mencattini, R. Lojacono, Federica Caselli, Paola Casti, Rangaraj M. Rangayyan, Simona Salicone, Corrado Di Natale, Gabriele Magna, A. Salsano and Berardino Sciunzi and has published in prestigious journals such as IEEE Transactions on Medical Imaging, IEEE Transactions on Fuzzy Systems and Applied Soft Computing.

In The Last Decade

Co-authorship network of co-authors of Marcello Salmeri i

Fields of papers citing papers by Marcello Salmeri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Marcello Salmeri

Since Specialization
Citations

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

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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2025