Emanuela Piciucco

12 total papers · 631 total citations
10 papers, 443 citations indexed

About

Emanuela Piciucco is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Cognitive Neuroscience. According to data from OpenAlex, Emanuela Piciucco has authored 10 papers receiving a total of 443 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Signal Processing, 5 papers in Computer Vision and Pattern Recognition and 3 papers in Cognitive Neuroscience. Recurrent topics in Emanuela Piciucco's work include Biometric Identification and Security (6 papers), EEG and Brain-Computer Interfaces (3 papers) and User Authentication and Security Systems (2 papers). Emanuela Piciucco is often cited by papers focused on Biometric Identification and Security (6 papers), EEG and Brain-Computer Interfaces (3 papers) and User Authentication and Security Systems (2 papers). Emanuela Piciucco collaborates with scholars based in Italy, Austria and Switzerland. Emanuela Piciucco's co-authors include Emanuele Maiorana, Patrizio Campisi, Rig Das, Christof Kauba, Andreas Uhl, Elena Di Lascio, Silvia Santini, Owen Falzon, Kenneth P. Camilleri and Marta Gomez‐Barrero and has published in prestigious journals such as Information Sciences, Pattern Recognition Letters and IEEE Transactions on Information Forensics and Security.

In The Last Decade

Emanuela Piciucco

10 papers receiving 430 citations

Author Peers

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

Author Last Decade Papers Cites
Emanuela Piciucco 345 200 128 82 42 10 443
Pedro Tome 372 1.1× 323 1.6× 94 0.7× 104 1.3× 16 0.4× 17 492
Sunpreet S. Arora 335 1.0× 161 0.8× 83 0.6× 113 1.4× 12 0.3× 21 443
Nesli Erdoğmuş 392 1.1× 375 1.9× 23 0.2× 122 1.5× 20 0.5× 14 479
Weijie Zhao 188 0.5× 200 1.0× 33 0.3× 95 1.2× 41 1.0× 17 472
Chiara Galdi 260 0.8× 239 1.2× 26 0.2× 165 2.0× 34 0.8× 28 445
Michael D. Indovina 343 1.0× 286 1.4× 24 0.2× 200 2.4× 11 0.3× 4 450
Kwang Yong Shin 192 0.6× 199 1.0× 34 0.3× 79 1.0× 23 0.5× 24 389
Hyeon Chang Lee 315 0.9× 185 0.9× 135 1.1× 78 1.0× 5 0.1× 10 372
Amioy Kumar 306 0.9× 257 1.3× 30 0.2× 193 2.4× 10 0.2× 32 445
Xianjing Meng 236 0.7× 239 1.2× 122 1.0× 38 0.5× 6 0.1× 21 479

Countries citing papers authored by Emanuela Piciucco

Since Specialization
Citations

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

Fields of papers citing papers by Emanuela Piciucco

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Emanuela Piciucco

This figure shows the co-authorship network connecting the top 25 collaborators of Emanuela Piciucco. A scholar is included among the top collaborators of Emanuela Piciucco 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 Emanuela Piciucco. Emanuela Piciucco 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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