Francesco Cricri

74 total papers · 875 total citations
41 papers, 450 citations indexed

About

Francesco Cricri is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Francesco Cricri has authored 41 papers receiving a total of 450 indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Computer Vision and Pattern Recognition, 14 papers in Signal Processing and 5 papers in Artificial Intelligence. Recurrent topics in Francesco Cricri's work include Advanced Image Processing Techniques (16 papers), Image and Signal Denoising Methods (10 papers) and Advanced Data Compression Techniques (9 papers). Francesco Cricri is often cited by papers focused on Advanced Image Processing Techniques (16 papers), Image and Signal Denoising Methods (10 papers) and Advanced Data Compression Techniques (9 papers). Francesco Cricri collaborates with scholars based in Finland, United States and Austria. Francesco Cricri's co-authors include Honglei Zhang, Esa Rahtu, Emre Aksu, Igor D. D. Curcio, Çağlar Aytekin, Hamed R. Tavakoli, Moncef Gabbouj, Miska M. Hannuksela, Yanlin Qian and Joni‐Kristian Kämäräinen and has published in prestigious journals such as IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Multimedia and Multimedia Tools and Applications.

In The Last Decade

Francesco Cricri

36 papers receiving 436 citations

Author Peers

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

Author Last Decade Papers Cites
Francesco Cricri 352 120 90 34 26 41 450
Alexandre R. J. François 381 1.1× 82 0.7× 76 0.8× 18 0.5× 22 0.8× 29 451
Jesús Bescós 361 1.0× 96 0.8× 106 1.2× 29 0.9× 12 0.5× 52 491
Dirk Farin 501 1.4× 236 2.0× 33 0.4× 24 0.7× 24 0.9× 35 546
Wen-Jiin Tsai 356 1.0× 121 1.0× 47 0.5× 15 0.4× 12 0.5× 45 487
Osamu Hori 486 1.4× 67 0.6× 47 0.5× 20 0.6× 13 0.5× 24 538
Niels Haering 386 1.1× 56 0.5× 120 1.3× 13 0.4× 43 1.7× 33 460
Youngmin Kim 270 0.8× 56 0.5× 70 0.8× 25 0.7× 23 0.9× 46 444
J.S. Jin 496 1.4× 148 1.2× 49 0.5× 44 1.3× 8 0.3× 46 541
David Gibbon 371 1.1× 147 1.2× 150 1.7× 86 2.5× 49 1.9× 42 547
Wen-Huang Cheng 296 0.8× 61 0.5× 129 1.4× 13 0.4× 25 1.0× 49 469

Countries citing papers authored by Francesco Cricri

Since Specialization
Citations

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

Fields of papers citing papers by Francesco Cricri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Francesco Cricri

This figure shows the co-authorship network connecting the top 25 collaborators of Francesco Cricri. A scholar is included among the top collaborators of Francesco Cricri 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 Francesco Cricri. Francesco Cricri 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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2026