Monica Mordonini

1.8k total citations · 1 hit paper
52 papers, 1.0k citations indexed

About

Monica Mordonini is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Monica Mordonini has authored 52 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 18 papers in Computer Vision and Pattern Recognition and 10 papers in Information Systems. Recurrent topics in Monica Mordonini's work include Spam and Phishing Detection (7 papers), Sentiment Analysis and Opinion Mining (7 papers) and Advanced Image and Video Retrieval Techniques (7 papers). Monica Mordonini is often cited by papers focused on Spam and Phishing Detection (7 papers), Sentiment Analysis and Opinion Mining (7 papers) and Advanced Image and Video Retrieval Techniques (7 papers). Monica Mordonini collaborates with scholars based in Italy and Germany. Monica Mordonini's co-authors include Ilaria De Munari, Gianfranco Lombardo, Stefano Cagnoni, Paolo Fornacciari, Valentina Bianchi, Marco Bassoli, Guido Matrella, Michele Tomaiuolo, Paolo Ciampolini and Agostino Poggi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computers in Human Behavior and IEEE Internet of Things Journal.

In The Last Decade

Monica Mordonini

50 papers receiving 983 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.

IoT Wearable Sensor and Deep Learning: An Integrated Approach for Personalized Human Activity Recognition in a Smart Home Environment

2019 316 citations Gianfranco Lombardo, Paolo Fornacciari et al. profile →

Peers

Monica Mordonini

CVPR

BE

AI

CNC

PHEOH

Amir Hajjam El Hassani France

Javier Medina-Quero Spain

Carolyn McGregor Canada

Abdur Rahim Mohammad Forkan Australia

Emmanuel Agu United States

James Jin Kang Australia

Pierre Rumeau France

Tianyi Zhang China

Tia Gao United States

Ivan Chorbev North Macedonia

Amir Hajjam El Hassani France

Monica Mordonini

181 ×0.5

CVPR

157 ×0.6

BE

244 ×1.1

AI

77 ×0.5

CNC

65 ×0.5

PHEOH

Citations per year, relative to Monica Mordonini Monica Mordonini (= 1×) peers Amir Hajjam El Hassani

Countries citing papers authored by Monica Mordonini

Since Specialization

Citations

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

Fields of papers citing papers by Monica Mordonini

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Monica Mordonini

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

All Works

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20 of 20 papers shown

1.

Lombardo, Gianfranco, Marco Picone, Marco Mamei, Monica Mordonini, & Agostino Poggi. (2023). Digital Twin for Continual Learning in Location Based Services. Engineering Applications of Artificial Intelligence. 127. 107203–107203. 13 indexed citations

2.

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

3.

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

4.

Bellini, Valentina, Marina Valente, Monica Mordonini, et al.. (2022). Machine learning in perioperative medicine: a systematic review. SHILAP Revista de lepidopterología. 2(1). 2–2. 46 indexed citations

5.

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

6.

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

7.

Bigliardi, Barbara, et al.. (2020). 人工知能:手術室管理における新しいツール手術室最適化における機械学習モデルの役割【JST・京大機械翻訳】. Journal of Medical Systems. 44(1). 1–10. 16 indexed citations

8.

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

9.

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

10.

Fornacciari, Paolo, Gianfranco Lombardo, Monica Mordonini, Agostino Poggi, & Michele Tomaiuolo. (2018). Agent based Cellular Automata Simulation. 2215. 16–20. 1 indexed citations

11.

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

12.

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

13.

Fornacciari, Paolo, Monica Mordonini, Agostino Poggi, & Michele Tomaiuolo. (2017). Software Actors for Continuous Social Media Analysis.. 84–89. 1 indexed citations

14.

Fornacciari, Paolo, et al.. (2017). Knowledge Discovery on Scopus.. 4 indexed citations

15.

Fornacciari, Paolo, Monica Mordonini, & Michele Tomaiuolo. (2015). A Case-Study for Sentiment Analysis on Twitter.. 53–58. 8 indexed citations

16.

Cagnoni, Stefano, et al.. (2009). Sensor Fusion-Oriented Fall Detection for Assistive Technologies Applications. 673–678. 16 indexed citations

17.

Adorni, Giovanni, Monica Mordonini, Stefano Cagnoni, & Antonio Sgorbissa. (2003). Omnidirectional stereo systems for robot navigation. CINECA IRIS Institutial Research Information System (University of Genoa). 79–79. 20 indexed citations

18.

Adorni, Giovanni, Stefano Cagnoni, Marco Gori, & Monica Mordonini. (2002). Access control system with neuro-fuzzy supervision. Use Siena air (University of Siena). 472–477. 9 indexed citations

19.

Adorni, Giovanni, et al.. (2002). Autonomous agents coordination through traffic signals and rules. 290–295. 4 indexed citations

20.

Mordonini, Monica & Agostino Poggi. (1999). SISTER: A Flexible System For Image Retrieval.. Informatica (slovenia). 23.

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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