Pasqualina Fragneto

621 citations
35 papers · 298 indexed · h-index 10
Topics
Cryptography and Residue Arithmetic (7 papers)Advanced Vision and Imaging (7 papers)Coding theory and cryptography (6 papers)
Journals
SHILAP Revista de lepidopterologíaPattern RecognitionComputer Vision and Image Understanding
Partner nations
ItalySwitzerlandCzechia

In The Last Decade

Pasqualina Fragneto

30 papers receiving 287 citations

Peers

Pasqualina Fragneto
Comparison fields: 5 of 54
  • Artificial Intelligence 153
  • Computer Vision and Pattern Recognition 114
  • Information Systems 49
  • Computer Networks and Communications 44
  • Aerospace Engineering 36
Replace Seong‐heum Kim with:
Seong‐heum Kim South Korea
Shulin Zeng China
Zhenbo Xu China
Pengfei Sun China
Cheng Wen China
Shivakumar Sastry United States
Vladimir V. Arlazarov Russia
Alkis Gotovos Switzerland
Pasqualina Fragneto relative to Seong‐heum Kim South Korea Seong‐heum Kim's profile →
Citations per field
00.5×10×15×
Seong‐heum Kim · 1×
Citations per year

Countries citing papers authored by Pasqualina Fragneto

Since Specialization
Citations

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

Fields of papers citing papers by Pasqualina Fragneto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pasqualina Fragneto

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 2
4 16
5 1
6
Approximate operations in Convolutional Neural Networks with RNS data representation.
5
7 8
8 2
9 6
10 25
11 3
12 1
13 0
14 12
15 2
16
Computing Tate Pairing on Smartcards
24
17 53
18 2
19 1
20 2

About Pasqualina Fragneto

Pasqualina Fragneto is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems, having authored 35 papers that have together received 298 indexed citations. Recurring topics across this work include Cryptography and Residue Arithmetic (7 papers), Advanced Vision and Imaging (7 papers) and Coding theory and cryptography (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (114 citations), Artificial Intelligence (153 citations) and Hardware and Architecture (26 citations). Pasqualina Fragneto has collaborated with scholars based in Italy, Switzerland and Czechia. Frequent co-authors include Beatrice Rossi, Guido Bertoni, Diego Carrera, Giacomo Boracchi, Andrea Fusiello, Federica Arrigoni, Marco Macchetti, Luca Negri, Gerardo Pelosi and Luca Breveglieri. Their work appears in journals such as SHILAP Revista de lepidopterología, Pattern Recognition and Computer Vision and Image Understanding.

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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