Francesco Sambo

1.1k total citations
37 papers, 450 citations indexed

About

Francesco Sambo is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Francesco Sambo has authored 37 papers receiving a total of 450 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 13 papers in Artificial Intelligence and 8 papers in Molecular Biology. Recurrent topics in Francesco Sambo's work include Advanced Neural Network Applications (8 papers), Video Surveillance and Tracking Methods (7 papers) and Bayesian Modeling and Causal Inference (6 papers). Francesco Sambo is often cited by papers focused on Advanced Neural Network Applications (8 papers), Video Surveillance and Tracking Methods (7 papers) and Bayesian Modeling and Causal Inference (6 papers). Francesco Sambo collaborates with scholars based in Italy, Spain and United States. Francesco Sambo's co-authors include Barbara Di Camillo, Claudio Cobelli, Leonardo Taccari, Samuele Salti, Gianna Toffolo, Matteo Borrotti, Kalliopi Mylona, Andrea Facchinetti, Giuseppe Fico and María Teresa Arredondo and has published in prestigious journals such as Bioinformatics, PLoS ONE and BMC Bioinformatics.

In The Last Decade

Francesco Sambo

33 papers receiving 427 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Francesco Sambo Italy 13 96 89 61 56 45 37 450
José-Luis Díez Spain 16 110 1.1× 122 1.4× 245 4.0× 30 0.5× 10 0.2× 93 903
Karan Verma India 13 96 1.0× 43 0.5× 25 0.4× 10 0.2× 59 1.3× 41 804
Yutaka Matsuo Japan 9 84 0.9× 40 0.4× 16 0.3× 11 0.2× 20 0.4× 41 467
Rafael Gomes Mantovani Brazil 12 239 2.5× 49 0.6× 8 0.1× 12 0.2× 6 0.1× 34 594
Itziar Irigoien Spain 11 89 0.9× 44 0.5× 32 0.5× 4 0.1× 5 0.1× 30 408
Jiajia Li China 9 118 1.2× 11 0.1× 31 0.5× 17 0.3× 10 0.2× 36 482
Taysir Hassan A. Soliman Egypt 11 215 2.2× 122 1.4× 4 0.1× 17 0.3× 4 0.1× 42 421
Hongfang Zhou China 8 241 2.5× 45 0.5× 5 0.1× 11 0.2× 9 0.2× 21 471

Countries citing papers authored by Francesco Sambo

Since Specialization
Citations

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

Fields of papers citing papers by Francesco Sambo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Francesco Sambo

This figure shows the co-authorship network connecting the top 25 collaborators of Francesco Sambo. A scholar is included among the top collaborators of Francesco Sambo 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 Francesco Sambo. Francesco Sambo 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.
Salti, Samuele, et al.. (2024). Dynamic Bird’s Eye View Reconstruction of Driving Accidents. IEEE Transactions on Intelligent Transportation Systems. 25(8). 8671–8680.
2.
Taccari, Leonardo, et al.. (2023). Cross-Model Temporal Cooperation Via Saliency Maps for Efficient Recognition and Classification of Relevant Traffic Lights. Florence Research (University of Florence). 2758–2763.
3.
Taccari, Leonardo, et al.. (2023). Cross-model temporal cooperation via saliency maps for efficient frame classification. Florence Research (University of Florence). 1156–1160. 1 indexed citations
4.
Sambo, Francesco, et al.. (2022). Lightweight and Effective Convolutional Neural Networks for Vehicle Viewpoint Estimation From Monocular Images. IEEE Transactions on Intelligent Transportation Systems. 24(1). 191–200. 2 indexed citations
5.
Taccari, Leonardo, et al.. (2022). Unsafe Maneuver Classification From Dashcam Video and GPS/IMU Sensors Using Spatio-Temporal Attention Selector. IEEE Transactions on Intelligent Transportation Systems. 23(9). 15605–15615. 5 indexed citations
6.
Borrotti, Matteo, Francesco Sambo, & Kalliopi Mylona. (2022). Multi-objective optimisation of split-plot designs. Econometrics and Statistics. 28. 163–172. 2 indexed citations
7.
Taccari, Leonardo, et al.. (2021). Deep Crash Detection From Vehicular Sensor Data With Multimodal Self-Supervision. IEEE Transactions on Intelligent Transportation Systems. 23(8). 12480–12489. 6 indexed citations
8.
Caprasecca, Stefano, et al.. (2021). Detection of Stop Sign Violations From Dashcam Data. IEEE Transactions on Intelligent Transportation Systems. 23(6). 5411–5420. 4 indexed citations
9.
Sambo, Francesco, et al.. (2020). A Lightweight Deep Learning Model for Vehicle Viewpoint Estimation from Dashcam Images. Florence Research (University of Florence). 1–6. 2 indexed citations
10.
Sambo, Francesco, Francesca Finotello, Enrico Lavezzo, et al.. (2018). Optimizing PCR primers targeting the bacterial 16S ribosomal RNA gene. BMC Bioinformatics. 19(1). 343–343. 46 indexed citations
11.
Jøsang, Audun, et al.. (2016). Bayesian deduction with subjective opinions. Principles of Knowledge Representation and Reasoning. 484–493. 4 indexed citations
12.
Sambo, Francesco, et al.. (2016). Vehicle Classification from Low Frequency GPS Data. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 1159–1166. 4 indexed citations
13.
Kaplan, Lance, et al.. (2015). Towards subjective networks: Extending conditional reasoning in subjective logic. International Conference on Information Fusion. 319–326. 3 indexed citations
14.
Marini, Simone, Nicola Barbarini, Francesco Sambo, et al.. (2015). A Dynamic Bayesian Network model for long-term simulation of clinical complications in type 1 diabetes. Journal of Biomedical Informatics. 57. 369–376. 38 indexed citations
15.
Fabris, Chiara, Andrea Facchinetti, Giuseppe Fico, et al.. (2015). Parsimonious Description of Glucose Variability in Type 2 Diabetes by Sparse Principal Component Analysis. Journal of Diabetes Science and Technology. 10(1). 119–124. 30 indexed citations
16.
Dagliati, Arianna, Lucia Sacchi, Mauro Bucalo, et al.. (2014). A data gathering framework to collect Type 2 diabetes patients data. Padua Research Archive (University of Padova). 244–247. 14 indexed citations
17.
Camillo, Barbara Di, et al.. (2012). Qualitative Reasoning for Biological Network Inference from Systematic Perturbation Experiments. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 9(5). 1482–1491. 2 indexed citations
18.
Sambo, Francesco, et al.. (2012). Bag of Naïve Bayes: biomarker selection and classification from genome-wide SNP data. BMC Bioinformatics. 13(S14). S2–S2. 23 indexed citations
19.
Sambo, Francesco, Marco A. Montes de, Barbara Di Camillo, Gianna Toffolo, & Thomas Stützle. (2012). MORE: Mixed Optimization for Reverse Engineering—An Application to Modeling Biological Networks Response via Sparse Systems of Nonlinear Differential Equations. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 9(5). 1459–1471. 6 indexed citations
20.
Camillo, Barbara Di, Tiziana Sanavia, Matteo Martini, et al.. (2012). Effect of Size and Heterogeneity of Samples on Biomarker Discovery: Synthetic and Real Data Assessment. PLoS ONE. 7(3). e32200–e32200. 23 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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