Luca Romeo

2.9k total citations · 1 hit paper
69 papers, 1.7k citations indexed

About

Luca Romeo is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Health Information Management. According to data from OpenAlex, Luca Romeo has authored 69 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 12 papers in Artificial Intelligence and 11 papers in Health Information Management. Recurrent topics in Luca Romeo's work include Artificial Intelligence in Healthcare (11 papers), Industrial Vision Systems and Defect Detection (9 papers) and Machine Learning in Healthcare (7 papers). Luca Romeo is often cited by papers focused on Artificial Intelligence in Healthcare (11 papers), Industrial Vision Systems and Defect Detection (9 papers) and Machine Learning in Healthcare (7 papers). Luca Romeo collaborates with scholars based in Italy, Ukraine and United Kingdom. Luca Romeo's co-authors include Emanuele Frontoni, Michele Bernardini, Adriano Mancini, Marina Paolanti, Francesco Ferracuti, Federica Verdini, Jelena Loncarski, Riccardo Rosati, Andrea Monteriù and Daniele Liciotti and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.

In The Last Decade

Luca Romeo

64 papers receiving 1.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

On the Integration of Artificial Intelligence and Blockchain Technology: A Perspective About Security

2024 49 citations Alexandr Kuznetsov, Luca Romeo et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Luca Romeo Italy	24	380	366	226	214	175	69	1.7k
Konstantinos Votis Greece	26	358 0.9×	419 1.1×	100 0.4×	92 0.4×	67 0.4×	201	2.4k
Iván García‐Magariño Spain	21	327 0.9×	182 0.5×	67 0.3×	53 0.2×	58 0.3×	106	1.5k
Ivan Miguel Pires Portugal	23	298 0.8×	488 1.3×	33 0.1×	67 0.3×	79 0.5×	156	1.9k
Mu‐Chun Su Taiwan	22	708 1.9×	515 1.4×	63 0.3×	256 1.2×	23 0.1×	113	1.8k
Antonio Coronato Italy	22	440 1.2×	292 0.8×	40 0.2×	90 0.4×	65 0.4×	95	1.4k
Fadel M. Megahed United States	24	274 0.7×	132 0.4×	292 1.3×	206 1.0×	53 0.3×	71	2.1k
Κωνσταντίνος Μουστάκας Greece	21	193 0.5×	428 1.2×	37 0.2×	93 0.4×	186 1.1×	189	1.6k
Andrea Monteriù Italy	23	250 0.7×	331 0.9×	221 1.0×	982 4.6×	18 0.1×	191	2.2k
Mohammad Shorfuzzaman Saudi Arabia	28	714 1.9×	510 1.4×	43 0.2×	48 0.2×	127 0.7×	108	2.3k
Chuan‐Jun Su Taiwan	17	137 0.4×	189 0.5×	177 0.8×	86 0.4×	33 0.2×	43	895

Countries citing papers authored by Luca Romeo

Since Specialization

Citations

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

Fields of papers citing papers by Luca Romeo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Luca Romeo

This figure shows the co-authorship network connecting the top 25 collaborators of Luca Romeo. A scholar is included among the top collaborators of Luca Romeo 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 Luca Romeo. Luca Romeo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Rosati, Riccardo, Luca Romeo, & Adriano Mancini. (2024). Single- and multi-task linear models for ATMs fault classification in human-centered predictive maintenance. Computers & Industrial Engineering. 200. 110763–110763.

Rosati, Riccardo, et al.. (2024). Learning Ordinal–Hierarchical Constraints for Deep Learning Classifiers. IEEE Transactions on Neural Networks and Learning Systems. 36(3). 4765–4778. 1 indexed citations

Sacheli, Lucia Maria, et al.. (2023). Visuo-motor interference is modulated by task interactivity: A kinematic study. Psychonomic Bulletin & Review. 30(5). 1788–1801. 4 indexed citations

Gutiérrez, Pedro Antonio, et al.. (2023). Exponential loss regularisation for encouraging ordinal constraint to shotgun stocks quality assessment. Applied Soft Computing. 138. 110191–110191. 11 indexed citations

Kuznetsov, Alexandr, et al.. (2023). Image steganalysis using deep learning models. Multimedia Tools and Applications. 83(16). 48607–48630. 4 indexed citations

Romeo, Luca, Temitayo Olugbade, Massimiliano Pontil, & Nadia Bianchi‐Berthouze. (2023). Multi-Rater Consensus Learning for Modeling Multiple Sparse Ratings of Affective Behaviour. IEEE Transactions on Affective Computing. 15(3). 859–871.

Rosati, Riccardo, et al.. (2023). A hybrid feature learning approach based on convolutional kernels for ATM fault prediction using event-log data. Engineering Applications of Artificial Intelligence. 123. 106463–106463. 10 indexed citations

Bernardini, Michele, et al.. (2023). A novel missing data imputation approach based on clinical conditional Generative Adversarial Networks applied to EHR datasets. Computers in Biology and Medicine. 163. 107188–107188. 18 indexed citations

Rosati, Riccardo, et al.. (2022). A novel deep ordinal classification approach for aesthetic quality control classification. Neural Computing and Applications. 34(14). 11625–11639. 20 indexed citations

10.

Gutiérrez, Pedro Antonio, et al.. (2022). Deep learning based hierarchical classifier for weapon stock aesthetic quality control assessment. Computers in Industry. 144. 103786–103786. 16 indexed citations

11.

Rosati, Riccardo, et al.. (2022). From knowledge-based to big data analytic model: a novel IoT and machine learning based decision support system for predictive maintenance in Industry 4.0. Journal of Intelligent Manufacturing. 34(1). 107–121. 104 indexed citations

12.

Cavallo, Andrea, Luca Romeo, Massimiliano Pontil, et al.. (2022). Decoding social decisions from movement kinematics. iScience. 25(12). 105550–105550. 6 indexed citations

13.

Calabrese, M., Luca Romeo, Silvia Ceccacci, et al.. (2020). SOPHIA: An Event-Based IoT and Machine Learning Architecture for Predictive Maintenance in Industry 4.0. Information. 11(4). 202–202. 95 indexed citations

14.

Rosati, Riccardo, Luca Romeo, Sonia Silvestri, et al.. (2020). Faster R-CNN approach for detection and quantification of DNA damage in comet assay images. Computers in Biology and Medicine. 123. 103912–103912. 34 indexed citations

15.

Romeo, Luca, Andrea Cavallo, Lucia Pepa, Nadia Bianchi‐Berthouze, & Massimiliano Pontil. (2019). Multiple Instance Learning for Emotion Recognition Using Physiological Signals. IEEE Transactions on Affective Computing. 13(1). 389–407. 35 indexed citations

16.

Bernardini, Michele, Micaela Morettini, Luca Romeo, Emanuele Frontoni, & Laura Burattini. (2019). TyG-er: An ensemble Regression Forest approach for identification of clinical factors related to insulin resistance condition using Electronic Health Records. Computers in Biology and Medicine. 112. 103358–103358. 23 indexed citations

17.

Capecci, Marianna, Maria Gabriella Ceravolo, Francesco Ferracuti, et al.. (2018). An instrumental approach for monitoring physical exercises in a visual markerless scenario: A proof of concept. Journal of Biomechanics. 69. 70–80. 29 indexed citations

18.

Cavallo, Andrea, Luca Romeo, Caterina Ansuini, et al.. (2018). Prospective motor control obeys to idiosyncratic strategies in autism. Scientific Reports. 8(1). 13717–13717. 18 indexed citations

19.

Capecci, Marianna, Maria Gabriella Ceravolo, Francesco Ferracuti, et al.. (2017). A Hidden Semi-Markov Model based approach for rehabilitation exercise assessment. Journal of Biomedical Informatics. 78. 1–11. 46 indexed citations

20.

Capecci, Marianna, Maria Gabriella Ceravolo, Francesco Ferracuti, et al.. (2016). Accuracy evaluation of the Kinect v2 sensor during dynamic movements in a rehabilitation scenario. PubMed. 2016. 5409–5412. 45 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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