Claudio Gennaro

3.6k total citations
108 papers, 1.5k citations indexed

About

Claudio Gennaro is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Claudio Gennaro has authored 108 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 75 papers in Computer Vision and Pattern Recognition, 33 papers in Artificial Intelligence and 30 papers in Computer Networks and Communications. Recurrent topics in Claudio Gennaro's work include Advanced Image and Video Retrieval Techniques (29 papers), Video Surveillance and Tracking Methods (18 papers) and Data Management and Algorithms (18 papers). Claudio Gennaro is often cited by papers focused on Advanced Image and Video Retrieval Techniques (29 papers), Video Surveillance and Tracking Methods (18 papers) and Data Management and Algorithms (18 papers). Claudio Gennaro collaborates with scholars based in Italy, Czechia and United States. Claudio Gennaro's co-authors include Giuseppe Amato, Fabrizio Falchi, Fabio Carrara, Claudio Vairo, Carlo Meghini, Pasquale Savino, Nicola Messina, Pavel Zezula, Luca Ciampi and Vlastislav Dohnal and has published in prestigious journals such as Expert Systems with Applications, Sensors and Cell Reports.

In The Last Decade

Claudio Gennaro

102 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Claudio Gennaro Italy 18 721 346 334 246 240 108 1.5k
Fabrizio Falchi Italy 21 987 1.4× 335 1.0× 627 1.9× 269 1.1× 186 0.8× 116 1.8k
Wisnu Jatmiko Indonesia 22 535 0.7× 156 0.5× 452 1.4× 99 0.4× 247 1.0× 226 1.9k
Mohana India 22 856 1.2× 106 0.3× 463 1.4× 146 0.6× 187 0.8× 94 1.6k
Giuseppe Amato Italy 24 1.4k 1.9× 348 1.0× 790 2.4× 273 1.1× 360 1.5× 150 2.7k
Francesco G. B. De Natale Italy 23 1.4k 1.9× 70 0.2× 373 1.1× 146 0.6× 157 0.7× 194 2.2k
Juan A. Álvarez-García Spain 16 502 0.7× 73 0.2× 257 0.8× 150 0.6× 109 0.5× 47 959
Xuemiao Xu China 21 1.3k 1.8× 259 0.7× 313 0.9× 238 1.0× 40 0.2× 83 1.9k
Fabio Carrara Italy 14 382 0.5× 323 0.9× 266 0.8× 222 0.9× 41 0.2× 45 898
Stewart Worrall Australia 23 1.2k 1.6× 273 0.8× 263 0.8× 212 0.9× 108 0.5× 158 2.1k
Pei Lv China 26 1.1k 1.5× 85 0.2× 494 1.5× 130 0.5× 89 0.4× 89 1.9k

Countries citing papers authored by Claudio Gennaro

Since Specialization
Citations

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

Fields of papers citing papers by Claudio Gennaro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Claudio Gennaro

This figure shows the co-authorship network connecting the top 25 collaborators of Claudio Gennaro. A scholar is included among the top collaborators of Claudio Gennaro 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 Claudio Gennaro. Claudio Gennaro 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.
Falchi, Fabrizio, et al.. (2024). Scalable bio-inspired training of Deep Neural Networks with FastHebb. Neurocomputing. 595. 127867–127867.
2.
Ciampi, Luca, Carlos Santiago, Fabrizio Falchi, Claudio Gennaro, & Giuseppe Amato. (2024). In the Wild Video Violence Detection: An Unsupervised Domain Adaptation Approach. SN Computer Science. 5(7). 1 indexed citations
3.
Amato, Giuseppe, Paolo Bolettieri, Fabio Carrara, et al.. (2024). Will VISIONE Remain Competitive in Lifelog Image Search?. ISTI Open Portal. 58–63. 1 indexed citations
4.
Coccomini, Davide Alessandro, Andrea Esuli, Fabrizio Falchi, Claudio Gennaro, & Giuseppe Amato. (2024). Detecting images generated by diffusers. PeerJ Computer Science. 10. e2127–e2127. 4 indexed citations
5.
Amato, Giuseppe, Paolo Bolettieri, Fabio Carrara, et al.. (2024). VISIONE 5.0: Toward Evaluation with Novice Users. ISTI Open Portal. 1–6.
6.
Amato, Giuseppe, Paolo Bolettieri, Fabio Carrara, et al.. (2023). VISIONE for newbies: an easier-to-use video retrieval system. ISTI Open Portal. 158–162. 5 indexed citations
7.
Coccomini, Davide Alessandro, Roberto Caldelli, Fabrizio Falchi, & Claudio Gennaro. (2023). On the Generalization of Deep Learning Models in Video Deepfake Detection. Journal of Imaging. 9(5). 89–89. 15 indexed citations
8.
Amato, Giuseppe, Paolo Bolettieri, Fabio Carrara, et al.. (2023). VISIONE: A Large-Scale Video Retrieval System with Advanced Search Functionalities. Zenodo (CERN European Organization for Nuclear Research). 649–653. 2 indexed citations
9.
Gotta, Alberto, et al.. (2023). Learning-Based Traffic Scheduling in Non-Stationary Multipath 5G Non-Terrestrial Networks. Remote Sensing. 15(7). 1842–1842. 3 indexed citations
10.
Benedetto, Marco Di, Fabio Carrara, Salvatore Nigro, et al.. (2022). Deep networks for behavioral variant frontotemporal dementia identification from multiple acquisition sources. Computers in Biology and Medicine. 148. 105937–105937. 7 indexed citations
11.
Ciampi, Luca, Nicola Messina, Claudio Gennaro, et al.. (2022). Bus Violence: An Open Benchmark for Video Violence Detection on Public Transport. Sensors. 22(21). 8345–8345. 17 indexed citations
12.
Ciampi, Luca, Fabio Carrara, Raffaele Mazziotti, et al.. (2022). Learning to count biological structures with raters’ uncertainty. Medical Image Analysis. 80. 102500–102500. 13 indexed citations
13.
Guarnera, Luca, Oliver Giudice, Alessandro Ortis, et al.. (2022). The Face Deepfake Detection Challenge. Journal of Imaging. 8(10). 263–263. 34 indexed citations
14.
Ciampi, Luca, Claudio Gennaro, Fabio Carrara, et al.. (2022). Multi-camera vehicle counting using edge-AI. Expert Systems with Applications. 207. 117929–117929. 18 indexed citations
15.
Messina, Nicola, Giuseppe Amato, Andrea Esuli, et al.. (2021). Fine-grained visual textual alignment for cross-modal retrieval using transformer encoders. CINECA IRIS Institutial research information system (University of Pisa). 88 indexed citations
16.
Messina, Nicola, Giuseppe Amato, Fabrizio Falchi, Claudio Gennaro, & Stéphane Marchand‐Maillet. (2021). Towards Efficient Cross-Modal Visual Textual Retrieval using Transformer-Encoder Deep Features. ISTI Open Portal. 5 indexed citations
17.
Carrara, Fabio, et al.. (2020). Combining GANs and AutoEncoders for efficient anomaly detection. ISTI Open Portal. 22 indexed citations
18.
Ferro, Erina, Claudio Gennaro, Alessandro Nordio, et al.. (2020). 5G-Enabled Security Scenarios for Unmanned Aircraft: Experimentation in Urban Environment. Drones. 4(2). 22–22. 10 indexed citations
19.
Barsocchi, Paolo, Antonello Calabrò, Erina Ferro, et al.. (2018). Boosting a Low-Cost Smart Home Environment with Usage and Access Control Rules. Sensors. 18(6). 1886–1886. 23 indexed citations
20.
Ciampi, Luca, Giuseppe Amato, Fabrizio Falchi, Claudio Gennaro, & Fausto Rabitti. (2018). Counting Vehicles with Cameras.. CINECA IRIS Institutial research information system (University of Pisa). 14 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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