Lucio Marcenaro

2.6k total citations
180 papers, 1.7k citations indexed

About

Lucio Marcenaro is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Lucio Marcenaro has authored 180 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 86 papers in Artificial Intelligence, 78 papers in Computer Vision and Pattern Recognition and 41 papers in Computer Networks and Communications. Recurrent topics in Lucio Marcenaro's work include Anomaly Detection Techniques and Applications (54 papers), Video Surveillance and Tracking Methods (48 papers) and Time Series Analysis and Forecasting (24 papers). Lucio Marcenaro is often cited by papers focused on Anomaly Detection Techniques and Applications (54 papers), Video Surveillance and Tracking Methods (48 papers) and Time Series Analysis and Forecasting (24 papers). Lucio Marcenaro collaborates with scholars based in Italy, Spain and United Kingdom. Lucio Marcenaro's co-authors include Carlo S. Regazzoni, Pietro Morerio, David Martín, Gian Luca Foresti, Mohamad Baydoun, Luca Marchesotti, G. Vernazza, Alejandro Betancourt, Matthias Rauterberg and Bernhard Rinner and has published in prestigious journals such as Proceedings of the IEEE, IEEE Transactions on Image Processing and IEEE Access.

In The Last Decade

Lucio Marcenaro

166 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lucio Marcenaro Italy 21 807 605 362 308 263 180 1.7k
Jiasi Chen United States 16 920 1.1× 411 0.7× 866 2.4× 530 1.7× 131 0.5× 51 2.0k
Pedro U. Lima Portugal 26 749 0.9× 493 0.8× 614 1.7× 235 0.8× 564 2.1× 181 2.1k
Juan‐Antonio Fernández‐Madrigal Spain 25 792 1.0× 435 0.7× 188 0.5× 453 1.5× 853 3.2× 67 1.8k
Paul Rad United States 22 373 0.5× 480 0.8× 526 1.5× 210 0.7× 90 0.3× 67 1.7k
Cipriano Galindo Spain 20 718 0.9× 406 0.7× 139 0.4× 267 0.9× 556 2.1× 70 1.7k
Barry Brumitt United States 15 1.9k 2.4× 346 0.6× 417 1.2× 492 1.6× 293 1.1× 22 2.5k
Luca Iocchi Italy 28 1.2k 1.5× 776 1.3× 529 1.5× 155 0.5× 625 2.4× 165 2.5k
Guohui Tian China 21 758 0.9× 320 0.5× 129 0.4× 187 0.6× 304 1.2× 176 1.5k
Joydeep Biswas United States 17 692 0.9× 360 0.6× 155 0.4× 263 0.9× 510 1.9× 77 1.4k
Zhihai He United States 21 1.1k 1.3× 221 0.4× 339 0.9× 364 1.2× 97 0.4× 86 1.7k

Countries citing papers authored by Lucio Marcenaro

Since Specialization
Citations

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

Fields of papers citing papers by Lucio Marcenaro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lucio Marcenaro

This figure shows the co-authorship network connecting the top 25 collaborators of Lucio Marcenaro. A scholar is included among the top collaborators of Lucio Marcenaro 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 Lucio Marcenaro. Lucio Marcenaro 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
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Adnan, Muhammad, Pamela Zontone, David Martín, Lucio Marcenaro, & Carlo S. Regazzoni. (2025). A Generative Model Approach for LiDAR-Based Classification and Ego Vehicle Localization Using Dynamic Bayesian Networks. Applied Sciences. 15(9). 5181–5181.
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Zontone, Pamela, et al.. (2025). Modeling Interactions Between Autonomous Agents in a Multi-Agent Self-Awareness Architecture. IEEE Transactions on Multimedia. 27. 5035–5049. 2 indexed citations
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Marcenaro, Lucio, et al.. (2024). Joint Data-Driven Analysis of Visual-Odometric Anomaly Signals in Generative Ai-Based Agents. CINECA IRIS Institutial Research Information System (University of Genoa). 264–268. 3 indexed citations
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Marcenaro, Lucio, et al.. (2022). A Kalman Variational Autoencoder Model Assisted by Odometric Clustering for Video Frame Prediction and Anomaly Detection. IEEE Transactions on Image Processing. 32. 415–429. 11 indexed citations
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Alam, Atm S., et al.. (2022). A Novel Resource Allocation for Anti-Jamming in Cognitive-UAVs: An Active Inference Approach. IEEE Communications Letters. 26(10). 2272–2276. 17 indexed citations
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Marín, Pablo, et al.. (2021). Modeling Perception in Autonomous Vehicles via 3D Convolutional Representations on LiDAR. IEEE Transactions on Intelligent Transportation Systems. 23(9). 14608–14619. 12 indexed citations
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Baydoun, Mohamad, et al.. (2021). Multilevel Anomaly Detection Through Variational Autoencoders and Bayesian Models for Self-Aware Embodied Agents. IEEE Transactions on Multimedia. 24. 1399–1414. 23 indexed citations
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Ravanbakhsh, Mahdyar, Mohamad Baydoun, Pablo Marín, et al.. (2020). Learning Self-Awareness for Autonomous Vehicles: Exploring Multisensory Incremental Models. IEEE Transactions on Intelligent Transportation Systems. 22(6). 3372–3386. 11 indexed citations
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Liu, Wei, et al.. (2020). Let There Be a Beam: Highlights From the 2020 IEEE Five-Minute Video Clip Contest [SP Competitions]. IEEE Signal Processing Magazine. 37(5). 157–162. 1 indexed citations
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Farrukh, Muhammad, et al.. (2020). AI-Based Abnormality Detection at the PHY-Layer of Cognitive Radio by Learning Generative Models. IEEE Transactions on Cognitive Communications and Networking. 6(1). 21–34. 40 indexed citations
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Tadesse, Girmaw Abebe, et al.. (2020). Privacy-Aware Human Activity Recognition From a Wearable Camera: Highlights From the IEEE Video And Image Processing Cup 2019 Student Competition [SP Competitions]. IEEE Signal Processing Magazine. 37(3). 168–172. 3 indexed citations
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Baydoun, Mohamad, Pablo Marín, David Martín, et al.. (2019). Learning Probabilistic Awareness Models for Detecting Abnormalities in Vehicle Motions. IEEE Transactions on Intelligent Transportation Systems. 21(3). 1308–1320. 10 indexed citations
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Marcenaro, Lucio, et al.. (2016). Activity recognition based on inertial sensors for Ambient Assisted Living. TU/e Research Portal. 371–378. 38 indexed citations
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Marcenaro, Lucio, et al.. (2016). Crowd analysis using visual and non-visual sensors, a survey. Queen Mary Research Online (Queen Mary University of London). 1249–1254. 17 indexed citations
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Morerio, Pietro, Lucio Marcenaro, & Carlo S. Regazzoni. (2014). A generative superpixel method. CINECA IRIS Institutial Research Information System (University of Genoa). 1–7. 7 indexed citations
20.
Morerio, Pietro, et al.. (2013). A bio-inspired knowledge representation method for anomaly detection in cognitive Video Surveillance systems. CINECA IRIS Institutial Research Information System (University of Genoa). 242–249. 6 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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