Roberto Prevete

2.0k total citations · 1 hit paper
63 papers, 1.1k citations indexed

About

Roberto Prevete is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Computer Vision and Pattern Recognition. According to data from OpenAlex, Roberto Prevete has authored 63 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Artificial Intelligence, 24 papers in Cognitive Neuroscience and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Roberto Prevete's work include EEG and Brain-Computer Interfaces (14 papers), Neural Networks and Applications (9 papers) and Action Observation and Synchronization (8 papers). Roberto Prevete is often cited by papers focused on EEG and Brain-Computer Interfaces (14 papers), Neural Networks and Applications (9 papers) and Action Observation and Synchronization (8 papers). Roberto Prevete collaborates with scholars based in Italy, France and Malta. Roberto Prevete's co-authors include Andrea Apicella, Francesco Isgrò, Francesco Donnarumma, Pasquale Arpaïa, Bernardo Magnini, Hristo Tanev, Matteo Negri, Nicola Moccaldi, Annarita Tedesco and Egidio De Benedetto and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Brain Research.

In The Last Decade

Roberto Prevete

59 papers receiving 1.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A survey on modern trainable activation functions

2021 322 citations Andrea Apicella, Francesco Donnarumma et al. Neural Networks profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Roberto Prevete Italy	16	403	236	125	119	108	63	1.1k
Xin Zhao China	21	313 0.8×	336 1.4×	120 1.0×	122 1.0×	190 1.8×	126	1.4k
Anikó Ekárt United Kingdom	16	313 0.8×	205 0.9×	175 1.4×	144 1.2×	55 0.5×	71	1.2k
Brett J. Borghetti United States	12	329 0.8×	158 0.7×	153 1.2×	77 0.6×	66 0.6×	56	773
Gyanendra K. Verma India	14	399 1.0×	340 1.4×	482 3.9×	133 1.1×	138 1.3×	37	1.6k
Kwee-Bo Sim South Korea	16	406 1.0×	354 1.5×	362 2.9×	145 1.2×	175 1.6×	178	1.4k
Naohiro Ishii Japan	16	265 0.7×	208 0.9×	174 1.4×	64 0.5×	78 0.7×	168	954
Austin J. Brockmeier United States	12	291 0.7×	273 1.2×	170 1.4×	162 1.4×	78 0.7×	44	1.1k
Tomoyuki Hiroyasu Japan	18	310 0.8×	84 0.4×	152 1.2×	55 0.5×	143 1.3×	162	1.1k
Haitao Gan China	15	354 0.9×	163 0.7×	255 2.0×	50 0.4×	62 0.6×	77	746
Galip Aydın Türkiye	17	365 0.9×	191 0.8×	225 1.8×	69 0.6×	47 0.4×	45	1.2k

Countries citing papers authored by Roberto Prevete

Since Specialization

Citations

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

Fields of papers citing papers by Roberto Prevete

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roberto Prevete

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

All Works

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20 of 20 papers shown

Isgrò, Francesco, et al.. (2025). SincVAE: A new semi-supervised approach to improve anomaly detection on EEG data using SincNet and variational autoencoder. SHILAP Revista de lepidopterología. 8. 100213–100213.

Apicella, Andrea, et al.. (2024). Interpreting the latent space of a Convolutional Variational Autoencoder for semi-automated eye blink artefact detection in EEG signals. Computer Standards & Interfaces. 92. 103897–103897. 1 indexed citations

Apicella, Andrea, Pasquale Arpaïa, Giovanni D’Errico, et al.. (2024). Toward cross-subject and cross-session generalization in EEG-based emotion recognition: Systematic review, taxonomy, and methods. Neurocomputing. 604. 128354–128354. 10 indexed citations

Prevete, Roberto, et al.. (2024). Enhancing EEG-Based MI-BCIs with Class-Specific and Subject-Specific Features Detected by Neural Manifold Analysis. Sensors. 24(18). 6110–6110.

Annuzzi, Giovanni, Andrea Apicella, Pasquale Arpaïa, et al.. (2023). Impact of Nutritional Factors in Blood Glucose Prediction in Type 1 Diabetes Through Machine Learning. IEEE Access. 11. 17104–17115. 18 indexed citations

Annuzzi, Giovanni, Andrea Apicella, Pasquale Arpaïa, et al.. (2023). Exploring Nutritional Influence on Blood Glucose Forecasting for Type 1 Diabetes Using Explainable AI. IEEE Journal of Biomedical and Health Informatics. 28(5). 3123–3133. 17 indexed citations

Apicella, Andrea, et al.. (2023). Adaptive filters in Graph Convolutional Neural Networks. Pattern Recognition. 144. 109867–109867. 17 indexed citations

Apicella, Andrea, Francesco Isgrò, & Roberto Prevete. (2023). Hidden classification layers: Enhancing linear separability between classes in neural networks layers. Pattern Recognition Letters. 177. 69–74. 2 indexed citations

Apicella, Andrea, Pasquale Arpaïa, Egidio De Benedetto, et al.. (2023). Employment of Domain Adaptation Techniques in SSVEP-Based Brain–Computer Interfaces. IEEE Access. 11. 36147–36157. 11 indexed citations

10.

Apicella, Andrea, et al.. (2023). On the effects of data normalization for domain adaptation on EEG data. Engineering Applications of Artificial Intelligence. 123. 106205–106205. 35 indexed citations

11.

Apicella, Andrea, et al.. (2022). Exploiting auto-encoders and segmentation methods for middle-level explanations of image classification systems. Knowledge-Based Systems. 255. 109725–109725. 11 indexed citations

12.

Apicella, Andrea, Francesco Donnarumma, Francesco Isgrò, & Roberto Prevete. (2021). A survey on modern trainable activation functions. Neural Networks. 138. 14–32. 322 indexed citations breakdown →

13.

Arpaïa, Pasquale, et al.. (2020). A Wearable EEG Instrument for Real-Time Frontal Asymmetry Monitoring in Worker Stress Analysis. IEEE Transactions on Instrumentation and Measurement. 69(10). 8335–8343. 101 indexed citations

14.

Apicella, Andrea, et al.. (2019). Explaining classification systems using sparse dictionaries.. The European Symposium on Artificial Neural Networks. 2 indexed citations

15.

Donnarumma, Francesco, Aniello Murano, & Roberto Prevete. (2015). Dynamic network functional comparison via approximate-bisimulation. Control and Cybernetics. 44(1). 3 indexed citations

16.

Montalto, Alessandro, et al.. (2015). Neural networks with non-uniform embedding and explicit validation phase to assess Granger causality. Neural Networks. 71. 159–171. 51 indexed citations

17.

Pezzulo, Giovanni, Francesco Donnarumma, Pierpaolo Iodice, Roberto Prevete, & Haris Dindo. (2015). The role of synergies within generative models of action execution and recognition: A computational perspective. Physics of Life Reviews. 12. 114–117. 4 indexed citations

18.

Magnini, Bernardo, Matteo Negri, Roberto Prevete, & Hristo Tanev. (2002). Towards Automatic Evaluation of Question/Answering Systems. Language Resources and Evaluation. 3 indexed citations

19.

Magnini, Bernardo, Matteo Negri, Roberto Prevete, & Hristo Tanev. (2002). Mining Knowledge from Repeated Co-Occurrences: DIOGENE at TREC 2002.. Text REtrieval Conference. 9 indexed citations

20.

Magnini, Bernardo, Matteo Negri, Roberto Prevete, & Hristo Tanev. (2002). Mining The Web To Validate Answers To Natural Language Questions. WIT transactions on information and communication technologies. 28. 1 indexed citations

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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