Corrado Mencar

2.1k total citations
73 papers, 981 citations indexed

About

Corrado Mencar is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Information Systems. According to data from OpenAlex, Corrado Mencar has authored 73 papers receiving a total of 981 indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Artificial Intelligence, 30 papers in Computational Theory and Mathematics and 14 papers in Information Systems. Recurrent topics in Corrado Mencar's work include Fuzzy Logic and Control Systems (38 papers), Rough Sets and Fuzzy Logic (28 papers) and Neural Networks and Applications (15 papers). Corrado Mencar is often cited by papers focused on Fuzzy Logic and Control Systems (38 papers), Rough Sets and Fuzzy Logic (28 papers) and Neural Networks and Applications (15 papers). Corrado Mencar collaborates with scholars based in Italy, Spain and Canada. Corrado Mencar's co-authors include Anna Maria Fanelli, Giovanna Castellano, Ciro Castiello, Gabriella Casalino, José M. Alonso, Gennaro Vessio, Nicoletta Del Buono, Luis Magdalena, Donato Lacedonia and Marco Mantero and has published in prestigious journals such as IEEE Access, BMC Bioinformatics and Information Sciences.

In The Last Decade

Corrado Mencar

68 papers receiving 939 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Corrado Mencar Italy 18 645 162 160 143 106 73 981
José M. Puerta Spain 19 819 1.3× 148 0.9× 171 1.1× 247 1.7× 221 2.1× 75 1.4k
Geok See Ng Singapore 15 398 0.6× 165 1.0× 47 0.3× 148 1.0× 46 0.4× 56 792
Fabio Cuzzolin United Kingdom 17 574 0.9× 298 1.8× 155 1.0× 406 2.8× 51 0.5× 75 1.1k
Steven A. Harp United States 13 550 0.9× 107 0.7× 55 0.3× 209 1.5× 183 1.7× 27 1.1k
Mohammad Saniee Abadeh Iran 19 946 1.5× 77 0.5× 74 0.5× 190 1.3× 241 2.3× 98 1.5k
María José Gacto Spain 14 1.1k 1.7× 178 1.1× 248 1.6× 60 0.4× 181 1.7× 33 1.3k
Alberto Bugarín Spain 20 772 1.2× 131 0.8× 236 1.5× 169 1.2× 195 1.8× 102 1.2k
Asim Roy United States 14 336 0.5× 70 0.4× 60 0.4× 123 0.9× 37 0.3× 49 608
Kenji Kira Japan 2 640 1.0× 46 0.3× 159 1.0× 331 2.3× 237 2.2× 2 1.3k
Víctor M. Rivas Spain 10 1.2k 1.9× 149 0.9× 385 2.4× 183 1.3× 191 1.8× 23 1.6k

Countries citing papers authored by Corrado Mencar

Since Specialization
Citations

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

Fields of papers citing papers by Corrado Mencar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Corrado Mencar

This figure shows the co-authorship network connecting the top 25 collaborators of Corrado Mencar. A scholar is included among the top collaborators of Corrado Mencar 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 Corrado Mencar. Corrado Mencar 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.
Mencar, Corrado, et al.. (2023). Density-based clustering with fully-convolutional networks for crowd flow detection from drones. Neurocomputing. 526. 169–179. 16 indexed citations
2.
Castellano, Giovanna, Ciro Castiello, Corrado Mencar, & Gennaro Vessio. (2020). Crowd Detection in Aerial Images Using Spatial Graphs and Fully-Convolutional Neural Networks. IEEE Access. 8. 64534–64544. 35 indexed citations
3.
Mencar, Corrado, Crescenzio Gallo, Marco Mantero, et al.. (2019). Application of machine learning to predict obstructive sleep apnea syndrome severity. Health Informatics Journal. 26(1). 298–317. 66 indexed citations
4.
Mencar, Corrado & Witold Pedrycz. (2019). GrCount: Counting method for uncertain data. MethodsX. 6. 2455–2459. 3 indexed citations
5.
Mencar, Corrado & Witold Pedrycz. (2019). Granular counting of uncertain data. Fuzzy Sets and Systems. 387. 108–126. 6 indexed citations
6.
Longo, Roberto, et al.. (2019). Identification and evaluation of cognitive deficits in schizophrenia using "Machine learning".. PubMed. 31(Suppl 3). 261–264. 6 indexed citations
7.
Alonso, José M., Alejandro Ramos-Soto, Ciro Castiello, & Corrado Mencar. (2018). Hybrid Data-Expert Explainable Beer Style Classifier. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 1–7. 4 indexed citations
8.
Castiello, Ciro, et al.. (2018). Interpretable fuzzy partitioning of classified data with variable granularity. Applied Soft Computing. 74. 567–582. 12 indexed citations
9.
Casalino, Gabriella, Giovanna Castellano, & Corrado Mencar. (2018). Incremental adaptive semi-supervised fuzzy clustering for data stream classification. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 1–7. 16 indexed citations
10.
Lisi, Francesca A. & Corrado Mencar. (2015). Towards fuzzy granulation in OWL ontologies.. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 144–158. 3 indexed citations
11.
Castiello, Ciro, et al.. (2015). Interpretable knowledge discovery from data with DC*. Advances in intelligent systems research. 3 indexed citations
12.
Mencar, Corrado, et al.. (2010). Interpretability assessment of fuzzy knowledge bases: A cointension based approach. International Journal of Approximate Reasoning. 52(4). 501–518. 57 indexed citations
13.
Mencar, Corrado, Ciro Castiello, & Anna Maria Fanelli. (2009). A logic-based approach for evaluating interpretability of fuzzy rule-based classifiers. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 339–344. 3 indexed citations
14.
Castellano, Giovanna, et al.. (2006). Classifying data with interpretable fuzzy granulation. 2006. 872–877. 6 indexed citations
15.
Mencar, Corrado, Giovanna Castellano, & Anna Maria Fanelli. (2005). Some Fundamental Interpretability Issues in Fuzzy Modeling. European Society for Fuzzy Logic and Technology Conference. 1. 100–105. 15 indexed citations
16.
Castellano, Giovanna, Anna Maria Fanelli, & Corrado Mencar. (2003). DCClass: a Tool to Extract Human Understandable Fuzzy Information Granules for Classification. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 376–379. 3 indexed citations
17.
Castellano, Giovanna, Anna Maria Fanelli, & Corrado Mencar. (2003). Design of transparent mamdani fuzzy inference systems. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 468–476. 20 indexed citations
18.
Castellano, Giovanna, Anna Maria Fanelli, & Corrado Mencar. (2003). Fuzzy Information Granules: a Compact, Transparent and Efficient Representation. Journal of Advanced Computational Intelligence and Intelligent Informatics. 7(2). 160–168. 7 indexed citations
19.
Castellano, Giovanna, Anna Maria Fanelli, & Corrado Mencar. (2002). Generation of interpretable fuzzy granules by a double-clustering technique. Archives of Control Sciences. 12(4). 397–410. 18 indexed citations
20.
Castellano, Giovanna, Anna Maria Fanelli, & Corrado Mencar. (2000). A New Empirical Risk Functional for a Neuro-Fuzzy Classifier. 3 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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