Gennaro Vessio

124 total papers · 1.5k total citations
51 papers, 754 citations indexed

About

Gennaro Vessio is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Gennaro Vessio has authored 51 papers receiving a total of 754 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Computer Vision and Pattern Recognition, 16 papers in Artificial Intelligence and 7 papers in Cognitive Neuroscience. Recurrent topics in Gennaro Vessio's work include Handwritten Text Recognition Techniques (10 papers), Parkinson's Disease Mechanisms and Treatments (6 papers) and Anomaly Detection Techniques and Applications (6 papers). Gennaro Vessio is often cited by papers focused on Handwritten Text Recognition Techniques (10 papers), Parkinson's Disease Mechanisms and Treatments (6 papers) and Anomaly Detection Techniques and Applications (6 papers). Gennaro Vessio collaborates with scholars based in Italy, Spain and Poland. Gennaro Vessio's co-authors include Giovanna Castellano, Donato Impedovo, Giuseppe Pirlo, Moises Díaz, Imran Siddiqi, Momina Moetesum, Corrado Mencar, Miguel A. Ferrer, Ciro Castiello and Eufemia Lella and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Expert Systems with Applications.

In The Last Decade

Gennaro Vessio

46 papers receiving 722 citations

Author Peers

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

Author						Papers	Cites
Gennaro Vessio	251	222	148	112	95	51	754
Gustavo Henrique de Rosa	198 0.8×	252 1.1×	219 1.5×	207 1.8×	51 0.5×	37	808
Francesco Fontanella	325 1.3×	315 1.4×	48 0.3×	37 0.3×	46 0.5×	57	741
V. Elamaran	103 0.4×	93 0.4×	105 0.7×	54 0.5×	77 0.8×	81	661
Aite Zhao	264 1.1×	103 0.5×	150 1.0×	101 0.9×	27 0.3×	28	737
Musa Peker	145 0.6×	177 0.8×	48 0.3×	113 1.0×	407 4.3×	26	849
Angelo Marcelli	430 1.7×	373 1.7×	69 0.5×	34 0.3×	85 0.9×	104	896
K. R. Seeja	144 0.6×	270 1.2×	95 0.6×	77 0.7×	195 2.1×	35	782
Tomas Krilavičius	119 0.5×	297 1.3×	21 0.1×	37 0.3×	37 0.4×	79	826
Michael A. Lones	49 0.2×	349 1.6×	153 1.0×	68 0.6×	66 0.7×	63	878
Jorge Munilla	111 0.4×	285 1.3×	56 0.4×	49 0.4×	109 1.1×	46	895

Countries citing papers authored by Gennaro Vessio

Since Specialization

Citations

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

Fields of papers citing papers by Gennaro Vessio

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gennaro Vessio

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