Alessandro Farasin

410 total citations
17 papers, 247 citations indexed

About

Alessandro Farasin is a scholar working on Safety, Risk, Reliability and Quality, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Alessandro Farasin has authored 17 papers receiving a total of 247 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Safety, Risk, Reliability and Quality, 6 papers in Global and Planetary Change and 5 papers in Environmental Engineering. Recurrent topics in Alessandro Farasin's work include Fire Detection and Safety Systems (6 papers), Fire effects on ecosystems (5 papers) and Air Quality Monitoring and Forecasting (2 papers). Alessandro Farasin is often cited by papers focused on Fire Detection and Safety Systems (6 papers), Fire effects on ecosystems (5 papers) and Air Quality Monitoring and Forecasting (2 papers). Alessandro Farasin collaborates with scholars based in Italy, Spain and Russia. Alessandro Farasin's co-authors include Paolo Garza, Nicola Linty, Alfredo Favenza, Fabio Dovis, Nikolai I. Petrov, Claudio Rossi, Tania Cerquitelli, Elena Baralis, Daniele Apiletti and Marco Grangetto and has published in prestigious journals such as IEEE Transactions on Aerospace and Electronic Systems, Applied Sciences and Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences.

In The Last Decade

Alessandro Farasin

16 papers receiving 235 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alessandro Farasin Italy 8 107 59 55 50 45 17 247
K. Brieß Germany 11 97 0.9× 176 3.0× 31 0.6× 22 0.4× 32 0.7× 48 333
Joshua Veitch-Michaelis United Kingdom 6 81 0.8× 74 1.3× 57 1.0× 29 0.6× 6 0.1× 12 262
Rainer Sandau Germany 9 41 0.4× 289 4.9× 63 1.1× 74 1.5× 9 0.2× 48 497
Tieding Lu China 10 27 0.3× 108 1.8× 12 0.2× 36 0.7× 9 0.2× 50 272
Jiangbo Xi China 10 38 0.4× 144 2.4× 14 0.3× 17 0.3× 10 0.2× 37 292
Marco Castronuovo Italy 7 123 1.1× 157 2.7× 116 2.1× 167 3.3× 21 0.5× 24 396
Liangtao Xu China 14 288 2.7× 20 0.3× 288 5.2× 28 0.6× 22 0.5× 37 469
Gwendoline Blanchet France 11 58 0.5× 161 2.7× 37 0.7× 36 0.7× 3 0.1× 38 404
Yifei Liu China 2 25 0.2× 56 0.9× 7 0.1× 44 0.9× 8 0.2× 7 244

Countries citing papers authored by Alessandro Farasin

Since Specialization
Citations

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

Fields of papers citing papers by Alessandro Farasin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alessandro Farasin

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

All Works

17 of 17 papers shown
1.
Farasin, Alessandro, et al.. (2022). A Dataset for Burned Area Delineation and Severity Estimation from Satellite Imagery. Proceedings of the 31st ACM International Conference on Information & Knowledge Management. 3893–3897. 11 indexed citations
2.
Farasin, Alessandro, et al.. (2021). Attention to Fires: Multi-Channel Deep Learning Models for Wildfire Severity Prediction. Applied Sciences. 11(22). 11060–11060. 21 indexed citations
3.
Apiletti, Daniele, et al.. (2021). Double-Step deep learning framework to improve wildfire severity classification.. 3 indexed citations
4.
Farasin, Alessandro, et al.. (2020). Supervised Burned Areas delineation by means of Sentinel-2 imagery and Convolutional Neural Networks. International Conference on Information Systems for Crisis Response and Management. 1060–1071. 4 indexed citations
5.
Farasin, Alessandro, et al.. (2020). A Comparative Analysis for Air Quality Estimation from Traffic and Meteorological Data. Applied Sciences. 10(13). 4587–4587. 16 indexed citations
6.
Farasin, Alessandro, et al.. (2020). Sentinel-1 Flood Delineation with Supervised Machine Learning. International Conference on Information Systems for Crisis Response and Management. 1072–1083. 1 indexed citations
7.
Farasin, Alessandro, et al.. (2020). Real-time Object Detection and Tracking in Mixed Reality using Microsoft HoloLens. Institutional Research Information System University of Turin (University of Turin). 165–172. 14 indexed citations
8.
Farasin, Alessandro, et al.. (2020). Double-Step U-Net: A Deep Learning-Based Approach for the Estimation of Wildfire Damage Severity through Sentinel-2 Satellite Data. Applied Sciences. 10(12). 4332–4332. 50 indexed citations
9.
Farasin, Alessandro, et al.. (2020). Deep Learning Models for Road Passability Detection during Flood Events Using Social Media Data. Applied Sciences. 10(24). 8783–8783. 13 indexed citations
10.
Farasin, Alessandro, et al.. (2019). Unsupervised Burned Area Estimation through Satellite Tiles: A multimodal approach by means of image segmentation over remote sensing imagery. 2466. 1–10. 3 indexed citations
11.
Rossi, Claudio, et al.. (2019). A Machine Learning Approach to Monitor Air Quality from Traffic and Weather Data.. 2492. 66–74. 2 indexed citations
12.
Farasin, Alessandro & Paolo Garza. (2018). PERCEIVE: Precipitation Data Characterization by means on Frequent Spatio-Temporal Sequences. Zenodo (CERN European Organization for Nuclear Research). 1081–1088.
13.
Linty, Nicola, Alessandro Farasin, Alfredo Favenza, & Fabio Dovis. (2018). Detection of GNSS Ionospheric Scintillations Based on Machine Learning Decision Tree. IEEE Transactions on Aerospace and Electronic Systems. 55(1). 303–317. 69 indexed citations
14.
Farasin, Alessandro, et al.. (2018). Deep Learning models for passability detection of flooded roads. Zenodo (CERN European Organization for Nuclear Research). 3 indexed citations
15.
Favenza, Alfredo, Alessandro Farasin, Nicola Linty, & Fabio Dovis. (2017). A Machine Learning Approach to GNSS Scintillation Detection: Automatic Soft Inspection of the Events. Proceedings of the Satellite Division's International Technical Meeting (Online). 4103–4111. 5 indexed citations
16.
Farasin, Alessandro, Cesare Marucchini, Lucio Minuti, Claudia Zadra, & A. Taticchi. (2005). GC/MS-SIM analysis of phenolic compounds in olive oil waste waters. Italian Journal of Food Science. 17(1). 83–88. 1 indexed citations
17.
Petrov, Nikolai I. & Alessandro Farasin. (2002). Assessment of protection system positioning and models using observations of lightning strikes to structures. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences. 458(2019). 723–742. 31 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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