Francesco Piccinno

10 papers and 79 indexed citations i.

About

Francesco Piccinno is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Francesco Piccinno has authored 10 papers receiving a total of 79 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 2 papers in Signal Processing. Recurrent topics in Francesco Piccinno’s work include Natural Language Processing Techniques (7 papers), Topic Modeling (7 papers) and Multimodal Machine Learning Applications (2 papers). Francesco Piccinno is often cited by papers focused on Natural Language Processing Techniques (7 papers), Topic Modeling (7 papers) and Multimodal Machine Learning Applications (2 papers). Francesco Piccinno collaborates with scholars based in Italy, United States and United Kingdom. Francesco Piccinno's co-authors include Paolo Ferragina, Yasemin Altün, Paweł Krzysztof Nowak, Peter Shaw, Julian Martin Eisenschlos, Marius Paşca, Mikhail Kozhevnikov, Daniele Pighin, Amit Gupta and Jonas Pfeiffer and has published in prestigious journals such as Computational Intelligence, CINECA IRIS Institutial research information system (University of Pisa) and arXiv (Cornell University).

In The Last Decade

Co-authorship network of co-authors of Francesco Piccinno i

Fields of papers citing papers by Francesco Piccinno

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Francesco Piccinno

Since Specialization
Citations

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