Francesco Sica

About

Francesco Sica is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Francesco Sica has authored 12 papers receiving a total of 72 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Information Systems and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Francesco Sica’s work include Cryptography and Residue Arithmetic (5 papers), Coding theory and cryptography (4 papers) and Chaos-based Image/Signal Encryption (3 papers). Francesco Sica is often cited by papers focused on Cryptography and Residue Arithmetic (5 papers), Coding theory and cryptography (4 papers) and Chaos-based Image/Signal Encryption (3 papers). Francesco Sica collaborates with scholars based in Singapore, Canada and United States. Francesco Sica's co-authors include Heng Huat Chan, S. Barry Cooper, Roberto Avanzi, Patrick Longa, Xinxin Fan, Mathieu Ciet, Guang Gong, Kwok‐Yan Lam, Cunsheng Ding and Torleiv Kløve and has published in prestigious journals such as Lecture notes in computer science, Discrete Applied Mathematics and Journal of Cryptology.

In The Last Decade

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

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Fields of papers citing papers by Francesco Sica

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Francesco Sica

Since Specialization

Citations

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