Angelo Marcelli

1.7k total citations
104 papers, 900 citations indexed

About

Angelo Marcelli is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Angelo Marcelli has authored 104 papers receiving a total of 900 indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Computer Vision and Pattern Recognition, 42 papers in Artificial Intelligence and 15 papers in Cognitive Neuroscience. Recurrent topics in Angelo Marcelli's work include Handwritten Text Recognition Techniques (40 papers), Evolutionary Algorithms and Applications (18 papers) and Image Retrieval and Classification Techniques (18 papers). Angelo Marcelli is often cited by papers focused on Handwritten Text Recognition Techniques (40 papers), Evolutionary Algorithms and Applications (18 papers) and Image Retrieval and Classification Techniques (18 papers). Angelo Marcelli collaborates with scholars based in Italy, Spain and Canada. Angelo Marcelli's co-authors include Claudio De Stefano, Antonio Della Cioppa, Antonio Parziale, Rosa Senatore, Giuseppe Boccignone, L.P. Cordella, Miguel A. Ferrer, A. Chianese, Moises Díaz and Francesco Fontanella and has published in prestigious journals such as Pattern Recognition, IEEE Transactions on Evolutionary Computation and Neurocomputing.

In The Last Decade

Angelo Marcelli

96 papers receiving 862 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Angelo Marcelli Italy 16 432 372 97 85 73 104 900
Claudio De Stefano Italy 18 477 1.1× 610 1.6× 125 1.3× 57 0.7× 42 0.6× 90 1.2k
Francesco Fontanella Italy 17 328 0.8× 323 0.9× 45 0.5× 48 0.6× 42 0.6× 57 764
Alessandra Scotto di Freca Italy 12 260 0.6× 220 0.6× 31 0.3× 41 0.5× 32 0.4× 35 539
Josef Scharinger Austria 15 250 0.6× 124 0.3× 42 0.4× 228 2.7× 60 0.8× 64 829
Gustavo Henrique de Rosa Brazil 12 200 0.5× 253 0.7× 18 0.2× 51 0.6× 16 0.2× 37 816
Gennaro Vessio Italy 17 256 0.6× 227 0.6× 10 0.1× 95 1.1× 39 0.5× 51 780
Ahmet Sertbaş Türkiye 13 276 0.6× 441 1.2× 17 0.2× 30 0.4× 18 0.2× 64 1.1k
Mounîm A. El‐Yacoubi France 20 544 1.3× 336 0.9× 12 0.1× 49 0.6× 63 0.9× 88 1.3k
Giorgio Roffo Italy 10 162 0.4× 224 0.6× 39 0.4× 52 0.6× 18 0.2× 17 494
Jzau‐Sheng Lin Taiwan 14 250 0.6× 190 0.5× 24 0.2× 111 1.3× 48 0.7× 42 590

Countries citing papers authored by Angelo Marcelli

Since Specialization
Citations

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

Fields of papers citing papers by Angelo Marcelli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Angelo Marcelli

This figure shows the co-authorship network connecting the top 25 collaborators of Angelo Marcelli. A scholar is included among the top collaborators of Angelo Marcelli 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 Angelo Marcelli. Angelo Marcelli 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
1.
Baldelli, Giulia, Claudia Gabucci, Giulia Amagliani, et al.. (2025). Integrated culture-based and molecular approach for the detection of three Arcobacter species in sushi and fresh vegetables. Food Microbiology. 132. 104843–104843.
2.
Senatore, Rosa, et al.. (2024). The onset of motor learning impairments in Parkinson’s disease: a computational investigation. Brain Informatics. 11(1). 4–4. 1 indexed citations
3.
Parziale, Antonio & Angelo Marcelli. (2024). Understanding upper-limb movements via neurocomputational models of the sensorimotor system and neurorobotics: where we stand. Artificial Intelligence Review. 57(3). 3 indexed citations
4.
Gregorio, Giuseppe De, et al.. (2023). End-to-End Transcript Alignment of 17th Century Manuscripts: The Case of Moccia Code. Journal of Imaging. 9(1). 17–17. 1 indexed citations
5.
Parziale, Antonio, et al.. (2023). Observation vs. interaction in the recognition of human-like movements. Frontiers in Robotics and AI. 10. 1112986–1112986. 2 indexed citations
6.
Cilia, Nicole Dalia, Giuseppe De Gregorio, Claudio De Stefano, et al.. (2022). Diagnosing Alzheimer’s disease from on-line handwriting: A novel dataset and performance benchmarking. Engineering Applications of Artificial Intelligence. 111. 104822–104822. 34 indexed citations
7.
Falco, Ivanoe De, et al.. (2021). Prediction of personalized blood glucose levels in type 1 diabetic patients using a neuroevolution approach. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 1708–1716. 7 indexed citations
8.
Parziale, Antonio, Rosa Senatore, Antonio Della Cioppa, & Angelo Marcelli. (2020). Cartesian genetic programming for diagnosis of Parkinson disease through handwriting analysis: Performance vs. interpretability issues. Artificial Intelligence in Medicine. 111. 101984–101984. 30 indexed citations
9.
10.
Malik, Muhammad Imran, Sheraz Ahmed, Angelo Marcelli, et al.. (2015). ICDAR2015 competition on signature verification and writer identification for on- and off-line skilled forgeries (SigWIcomp2015). Griffith Research Online (Griffith University, Queensland, Australia). 1186–1190. 37 indexed citations
11.
Parziale, Antonio, et al.. (2015). Stability, Speed and Accuracy for Online Signature Verification. 18(2). 39–49. 2 indexed citations
12.
Stefano, Claudio De, Antonio Della Cioppa, & Angelo Marcelli. (2013). Evolutionary approaches for pooling classifier ensembles: Performance evaluation. 16. 309–314. 1 indexed citations
13.
Cordella, L.P., Claudio De Stefano, Francesco Fontanella, & Angelo Marcelli. (2013). EvoGeneSys, a new evolutionary approach to graph generation. Applied Soft Computing. 13(4). 1922–1938. 1 indexed citations
14.
Boccignone, Giuseppe, et al.. (2008). Bayesian Integration of Face and Low-Level Cues for Foveated Video Coding. IEEE Transactions on Circuits and Systems for Video Technology. 18(12). 1727–1740. 33 indexed citations
15.
Stefano, Claudio De, C. D'Elia, Angelo Marcelli, & Alessandra Scotto di Freca. (2007). Using Bayesian Network for combining classifiers. 73–80. 2 indexed citations
16.
Stefano, Claudio De, et al.. (2004). On the Role of Population Size and Niche Radius in Fitness Sharing. IEEE Transactions on Evolutionary Computation. 8(6). 580–592. 59 indexed citations
17.
Cordella, L.P., Claudio De Stefano, Antonio Della Cioppa, & Angelo Marcelli. (2003). A new evolutionary learning model for handwritten character prototyping. 27 28. 830–835. 1 indexed citations
18.
Marcelli, Angelo, et al.. (2002). Machine learning and genetic algorithms: an application to character recognition. 3. 2225–2230. 4 indexed citations
19.
Stefano, Claudio De & Angelo Marcelli. (2002). Generalization vs. specialization: quantitative evaluation criteria for genetics-based learning systems. 3. 2865–2870. 5 indexed citations
20.
Marcelli, Angelo & Theo Pavlidis. (1994). <title>Using projections for preclassification of character shape</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 2181. 4–13. 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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