Stefano Cagnoni

3.2k total citations
116 papers, 1.8k citations indexed

About

Stefano Cagnoni is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Stefano Cagnoni has authored 116 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Artificial Intelligence, 33 papers in Computer Vision and Pattern Recognition and 10 papers in Molecular Biology. Recurrent topics in Stefano Cagnoni's work include Evolutionary Algorithms and Applications (29 papers), Metaheuristic Optimization Algorithms Research (22 papers) and Advanced Image and Video Retrieval Techniques (13 papers). Stefano Cagnoni is often cited by papers focused on Evolutionary Algorithms and Applications (29 papers), Metaheuristic Optimization Algorithms Research (22 papers) and Advanced Image and Video Retrieval Techniques (13 papers). Stefano Cagnoni collaborates with scholars based in Italy, United Kingdom and Spain. Stefano Cagnoni's co-authors include Riccardo Poli, G. Valli, Monica Mordonini, Luca Mussi, Fabio Daolio, Pablo Mesejo, Guido Matrella, Ilaria De Munari, Paolo Ciampolini and Giovanni Adorni and has published in prestigious journals such as PLoS ONE, IEEE Access and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Stefano Cagnoni

112 papers receiving 1.7k citations

Peers

Stefano Cagnoni

CVPR

CCM

CTM

Asha Rani India

Fuqian Shi China

Alan Jović Croatia

Wei Peng United States

Prashant Kumar Shukla India

Patricia Bradley United States

Adi Alhudhaif Saudi Arabia

İbrahim Türkoğlu Türkiye

Zhaohong Deng China

Abeer D. Algarni Saudi Arabia

Asha Rani India

Stefano Cagnoni

789 ×1.3

315 ×0.6

CVPR

430 ×1.4

140 ×0.7

CCM

268 ×1.5

CTM

Citations per year, relative to Stefano Cagnoni Stefano Cagnoni (= 1×) peers Asha Rani

Countries citing papers authored by Stefano Cagnoni

Since Specialization

Citations

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

Fields of papers citing papers by Stefano Cagnoni

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stefano Cagnoni

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

Bacardit, Jaume, Alexander E. I. Brownlee, Stefano Cagnoni, et al.. (2024). Evolutionary Computation and Explainable AI: A Roadmap to Understandable Intelligent Systems. IEEE Transactions on Evolutionary Computation. 29(5). 2213–2228. 6 indexed citations

Bianchi, Valentina, Stefano Cagnoni, Andrea Boni, et al.. (2024). Model-Based design of a Machine Learning algorithm for on-site food authenticity testing. 43–47. 1 indexed citations

Lombardo, Gianfranco, et al.. (2024). A Multi-Head LSTM Architecture for Bankruptcy Prediction with Time Series Accounting Data. Future Internet. 16(3). 79–79. 1 indexed citations

Lombardo, Gianfranco, et al.. (2024). Language Models Fine-Tuning for Automatic Format Reconstruction of SEC Financial Filings. IEEE Access. 12. 31249–31261. 1 indexed citations

Fortunati, Simone, Monica Mattarozzi, Andrea Boni, et al.. (2024). Evaluation of a Voltametric E-Tongue Combined with Data Preprocessing for Fast and Effective Machine Learning-Based Classification of Tomato Purées by Cultivar. Sensors. 24(11). 3586–3586. 5 indexed citations

Cagnoni, Stefano, et al.. (2022). Automatic Detection of Sensitive Data Using Transformer- Based Classifiers. Future Internet. 14(8). 228–228. 8 indexed citations

Lombardo, Gianfranco, et al.. (2022). Machine Learning for Bankruptcy Prediction in the American Stock Market: Dataset and Benchmarks. Future Internet. 14(8). 244–244. 24 indexed citations

Lombardo, Gianfranco, Michele Tomaiuolo, Stefano Cagnoni, et al.. (2022). Fine-Grained Agent-Based Modeling to Predict Covid-19 Spreading and Effect of Policies in Large-Scale Scenarios. IEEE Journal of Biomedical and Health Informatics. 26(5). 2052–2062. 13 indexed citations

Lombardo, Gianfranco, et al.. (2022). High-Performance Computing and ABMS for High-Resolution COVID-19 Spreading Simulation. Future Internet. 14(3). 83–83. 2 indexed citations

10.

Amoretti, Michele, et al.. (2021). ReSS: A tool for discovering relevant sets in complex systems. SoftwareX. 14. 100693–100693. 1 indexed citations

11.

Tomaiuolo, Michele, Gianfranco Lombardo, Monica Mordonini, Stefano Cagnoni, & Agostino Poggi. (2020). A Survey on Troll Detection. Future Internet. 12(2). 31–31. 19 indexed citations

12.

Pecori, Riccardo, et al.. (2019). From Complex System Analysis to Pattern Recognition: Experimental Assessment of an Unsupervised Feature Extraction Method Based on the Relevance Index Metrics. Computation. 7(3). 39–39. 3 indexed citations

13.

Cagnoni, Stefano, et al.. (2019). What Can We Learn from Multi-Objective Meta-Optimization of Evolutionary Algorithms in Continuous Domains?. Mathematics. 7(3). 232–232. 8 indexed citations

14.

Villani, Marco, Riccardo Pecori, Michele Amoretti, et al.. (2018). An Iterative Information‐Theoretic Approach to the Detection of Structures in Complex Systems. Complexity. 2018(1). 11 indexed citations

15.

Cagnoni, Stefano & Mauro Castelli. (2018). Special Issue on Computational Intelligence and Nature-Inspired Algorithms for Real-World Data Analytics and Pattern Recognition. Algorithms. 11(3). 25–25. 1 indexed citations

16.

Matrella, Guido, et al.. (2017). Automatic diet monitoring: a review of computer vision and wearable sensor-based methods. International Journal of Food Sciences and Nutrition. 68(6). 656–670. 60 indexed citations

17.

Matrella, Guido, et al.. (2017). A New Approach to Image-Based Estimation of Food Volume. Algorithms. 10(2). 66–66. 23 indexed citations

18.

Cagnoni, Stefano, et al.. (2013). Design of a Wearable Sensing System for Human Motion Monitoring in Physical Rehabilitation. Sensors. 13(6). 7735–7755. 29 indexed citations

19.

Raidl, Günther R., Stefano Cagnoni, Juan Romero, et al.. (2003). Applications of Evolutionary Computing: Evoworkshops 2003. Springer eBooks. 49 indexed citations

20.

Cagnoni, Stefano, et al.. (2000). Real-world applications of evolutionary computing : EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoRob, and EvoFlight, Edinburgh, Scotland, UK, April 17, 2000 : proceedings. Springer eBooks. 2 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.

Explore authors with similar magnitude of impact