Andrea Ranieri
I received the M.Sc. Degree in Computer Engineering from the University of Genova in 2006 and the Ph.D. in Space Science and Engineering in 2012. I’m currently employed as full-time researcher at the Institute for Applied Mathematics and Information Technologies “Enrico Magenes” (IMATI) unit of Genova, of the National Research Council of Italy (CNR).
My academic education in Computer Engineering had a strong focus on networking and distributed systems, but for the last seven years I’ve been working also on real-time systems, robotics and automation. My current research interests are mainly in the field of Deep Learning for Computer Vision, Natural Language Processing (NLP) or Time Series Forecasting.
My technical background is extremely diverse with ten years’ experience working with Linux in almost all of its main flavours and excellent coding skills, both with traditional languages such as C/C++ and scripting languages such as Python or just the Linux Bash.
Research Activity
Deep Learning Computer Vision Distributed Systems Software & Languages
Ongoing Projects
PITSTOP
ProMED
5G Genova
Publications
2022, Journal article
SHREC 2022: Pothole and crack detection in the road pavement using images and RGB-D data
E. Moscoso Thompson, A.Ranieri, S. Biasotti, M. Chicchon, I.Sipiran I, M.-K. Pham, T.-L. Nguyen-Ho, H.-D. Nguyen, M.-T. Tran
This paper describes the methods submitted for evaluation to the SHREC 2022 track on pothole and crack detection in the road pavement. A total of 7 different runs for the semantic segmentation of the ...
CNR@People | DOI: 10.1016/j.cag.2022.07.018
2021, Journal article
Deep Adversarial Learning on Google Home Devices
Andrea Ranieri, Davide Caputo, Luca Verderame, Alessio Merlo, Luca Caviglione
Smart speakers and voice-based virtual assistants are core components for the success of the IoT paradigm. Unfortunately, they are vulnerable to various privacy threats exploiting machine learning to ...
CNR@People | DOI: 10.22667/JISIS.2021.11.30.033
2021, Journal article
SHREC 2021: Skeleton-based hand gesture recognition in the wild
A. Caputo, A. Giachetti, S. Soso, D. Pintani, A. D'Eusanio, S. Pini, G. Borghi, A. Simoni, R. Vezzani, R. Cucchiara, A. Ranieri, F. Giannini, K. Lupinetti, M. Monti, M. Maghoumi, J.J. LaViola Jr, M.-Q. Le, H.-D. Nguyen, M.-T. Tran
Gesture recognition is a fundamental tool to enable novel interaction paradigms in a variety of application scenarios like Mixed Reality environments, touchless public kiosks, entertainment systems, a...
CNR@People | DOI: 10.1016/j.cag.2021.07.007
2021, Journal article
Underwater Vision-Based Gesture Recognition: A Robustness Validation for Safe Human-Robot Interaction
Gomez Chavez, Arturo; Ranieri, Andrea; Chiarella, Davide; Birk, Andreas
Underwater robotics requires very reliable and safe operations. This holds especially for missions in cooperation with divers who are - despite the significant advancements of marine robotics in recen...
CNR@People | DOI: 10.1109/MRA.2021.3075560
2020, Journal article
Fine-hearing Google Home: why silence will not protect your privacy
Davide Caputo, Luca Verderame, Andrea Ranieri, Alessio Merlo, Luca Caviglione
Smart speakers and voice-based virtual assistants are used to retrieve information, interact with other devices, and command a variety of Internet of Things (IoT) nodes. To this aim, smart speakers an...
CNR@People | DOI: 10.22667/JOWUA.2020.03.31.035
2020, Journal article
SFINGE 3D: A novel benchmark for online detection and recognition of heterogeneous hand gestures from 3D fingers' trajectories
A. Caputo, A. Giachetti, F. Giannini, K. Lupinetti, M. Monti, M. Pegoraro, A. Ranieri
In recent years gesture recognition has become an increasingly interesting topic for both research and industry. While interaction with a device through a gestural interface is a promising idea in sev...
CNR@People | DOI: 10.1016/j.cag.2020.07.014
2019, Journal article
CADDY Underwater Stereo-Vision Dataset for Human-Robot Interaction (HRI) in the Context of Diver Activities
Arturo Gomez Chavez, Andrea Ranieri, Davide Chiarella, Enrica Zereik, Anja Babi?, Andreas Birk
In this article, we present a novel underwater dataset collected from several field trials within the EU FP7 project "Cognitive autonomous diving buddy (CADDY)", where an Autonomous Underwat...
CNR@People | DOI: 10.3390/jmse7010016
2018, Journal article
A Novel Gesture-Based Language for Underwater Human-Robot Interaction
Chiarella, Davide; Bibuli, Marco; Bruzzone, Gabriele; Caccia, Massimo; Ranieri, Andrea; Zereik, Enrica; Marconi, Lucia; Cutugno, Paola
The underwater environment is characterized by hazardous conditions that make it difficult to manage and monitor even the simplest human operation. The introduction of a robot companion with the task ...
CNR@People | DOI: 10.3390/jmse6030091
2017, Journal article
Cooperative adaptive guidance and control paradigm for marine robots in an emergency ship towing scenario
Bruzzone, G.; Bibuli, M.; Zereik, E.; Ranieri, A.; Caccia, M.
This paper focuses on the control strategy needed by marine robots to be able to follow moving paths within a cooperative framework. This control aspect is essential in order to effectively perform em...
CNR@People | DOI: 10.1002/acs.2667
2015, Journal article
Testing the Waters: Design of Replicable Experiments for Performance Assessment of Marine Robotic Platforms
Sorbara, Andrea; Ranieri, Andrea; Saggini, Eleonora; Zereik, Enrica; Bibuli, Marco; Bruzzone, Gabriele; Riccomagno, Eva; Caccia, Massimo
Robotics is becoming part of our daily life through home automation (called domotic) and assistive applications that are taking place in habitations, up to industrial and service employments. With thi...
CNR@People | DOI: 10.1109/MRA.2015.2448311
SHREC 2022: Pothole and crack detection in the road pavement using images and RGB-D data
E. Moscoso Thompson, A.Ranieri, S. Biasotti, M. Chicchon, I.Sipiran I, M.-K. Pham, T.-L. Nguyen-Ho, H.-D. Nguyen, M.-T. Tran
This paper describes the methods submitted for evaluation to the SHREC 2022 track on pothole and crack detection in the road pavement. A total of 7 different runs for the semantic segmentation of the ...
CNR@People | DOI: 10.1016/j.cag.2022.07.018
2021, Journal article
Deep Adversarial Learning on Google Home Devices
Andrea Ranieri, Davide Caputo, Luca Verderame, Alessio Merlo, Luca Caviglione
Smart speakers and voice-based virtual assistants are core components for the success of the IoT paradigm. Unfortunately, they are vulnerable to various privacy threats exploiting machine learning to ...
CNR@People | DOI: 10.22667/JISIS.2021.11.30.033
2021, Journal article
SHREC 2021: Skeleton-based hand gesture recognition in the wild
A. Caputo, A. Giachetti, S. Soso, D. Pintani, A. D'Eusanio, S. Pini, G. Borghi, A. Simoni, R. Vezzani, R. Cucchiara, A. Ranieri, F. Giannini, K. Lupinetti, M. Monti, M. Maghoumi, J.J. LaViola Jr, M.-Q. Le, H.-D. Nguyen, M.-T. Tran
Gesture recognition is a fundamental tool to enable novel interaction paradigms in a variety of application scenarios like Mixed Reality environments, touchless public kiosks, entertainment systems, a...
CNR@People | DOI: 10.1016/j.cag.2021.07.007
2021, Journal article
Underwater Vision-Based Gesture Recognition: A Robustness Validation for Safe Human-Robot Interaction
Gomez Chavez, Arturo; Ranieri, Andrea; Chiarella, Davide; Birk, Andreas
Underwater robotics requires very reliable and safe operations. This holds especially for missions in cooperation with divers who are - despite the significant advancements of marine robotics in recen...
CNR@People | DOI: 10.1109/MRA.2021.3075560
2020, Journal article
Fine-hearing Google Home: why silence will not protect your privacy
Davide Caputo, Luca Verderame, Andrea Ranieri, Alessio Merlo, Luca Caviglione
Smart speakers and voice-based virtual assistants are used to retrieve information, interact with other devices, and command a variety of Internet of Things (IoT) nodes. To this aim, smart speakers an...
CNR@People | DOI: 10.22667/JOWUA.2020.03.31.035
2020, Journal article
SFINGE 3D: A novel benchmark for online detection and recognition of heterogeneous hand gestures from 3D fingers' trajectories
A. Caputo, A. Giachetti, F. Giannini, K. Lupinetti, M. Monti, M. Pegoraro, A. Ranieri
In recent years gesture recognition has become an increasingly interesting topic for both research and industry. While interaction with a device through a gestural interface is a promising idea in sev...
CNR@People | DOI: 10.1016/j.cag.2020.07.014
2019, Journal article
CADDY Underwater Stereo-Vision Dataset for Human-Robot Interaction (HRI) in the Context of Diver Activities
Arturo Gomez Chavez, Andrea Ranieri, Davide Chiarella, Enrica Zereik, Anja Babi?, Andreas Birk
In this article, we present a novel underwater dataset collected from several field trials within the EU FP7 project "Cognitive autonomous diving buddy (CADDY)", where an Autonomous Underwat...
CNR@People | DOI: 10.3390/jmse7010016
2018, Journal article
A Novel Gesture-Based Language for Underwater Human-Robot Interaction
Chiarella, Davide; Bibuli, Marco; Bruzzone, Gabriele; Caccia, Massimo; Ranieri, Andrea; Zereik, Enrica; Marconi, Lucia; Cutugno, Paola
The underwater environment is characterized by hazardous conditions that make it difficult to manage and monitor even the simplest human operation. The introduction of a robot companion with the task ...
CNR@People | DOI: 10.3390/jmse6030091
2017, Journal article
Cooperative adaptive guidance and control paradigm for marine robots in an emergency ship towing scenario
Bruzzone, G.; Bibuli, M.; Zereik, E.; Ranieri, A.; Caccia, M.
This paper focuses on the control strategy needed by marine robots to be able to follow moving paths within a cooperative framework. This control aspect is essential in order to effectively perform em...
CNR@People | DOI: 10.1002/acs.2667
2015, Journal article
Testing the Waters: Design of Replicable Experiments for Performance Assessment of Marine Robotic Platforms
Sorbara, Andrea; Ranieri, Andrea; Saggini, Eleonora; Zereik, Enrica; Bibuli, Marco; Bruzzone, Gabriele; Riccomagno, Eva; Caccia, Massimo
Robotics is becoming part of our daily life through home automation (called domotic) and assistive applications that are taking place in habitations, up to industrial and service employments. With thi...
CNR@People | DOI: 10.1109/MRA.2015.2448311
2022, Conference proceedings
Monitoraggio dello stato del manto stradale usando tecniche di deep learning
Andrea Ranieri, Silvia Biasotti, Elia Moscoso Thompson, Michela Spagnuolo
Questo documento riassume il contributo IMATIallo sviluppo di metodi per il riconoscimento di ammaloramentidel manto stradale, quali buche, crepe,cedimenti attraverso tecniche di deep learning. Talico...
CNR@People | Link
2021, Conference proceedings
Automatic segmentation of archaeological fragments with relief patterns using convolutional neural networks
E. Moscoso Thompson, A. Ranieri, S. Biasotti
The recent commodification of high-quality 3D scanners is leading to the possibility of capturing models of archaeological findsand automatically recognizing their surface reliefs. We present our adva...
CNR@People | DOI: 10.2312/gch.20211411
2020, Conference proceedings
3D dynamic hand gestures recognition using the leap motion sensor and convolutional neural networks
K. Lupinetti, A. Ranieri, F. Giannini, M. Monti
Defining methods for the automatic understanding of gestures is of paramount importance in many application contexts and in Virtual Reality applications for creating more natural and easy-to-use human...
CNR@People | DOI: 10.1007/978-3-030-58465-8_31
2020, Conference proceedings
Are you (Google) Home? Detecting Users Presence through Traffic Analysis of Smart Speakers
D. Caputo, L. Verderame, A. Merlo, A. Ranieri and L. Caviglione
Smart speakers and voice-based virtual assistants are core building blocks of modern smart homes. For instance, they are used to retrieve information, interact with other devices, and command a variet...
CNR@People | Link
2019, Conference posters
Marine robotics for sampling air-sea-ice interface in the Arctic region
Massimo Caccia, Roberta Ferretti, Angelo Odetti, Andrea Ranieri, Giorgio Bruzzone, Edoardo Spirandelli, and Gabriele Bruzzone
Although chemical-physical characterization of air and water columns in the proximity of fronts/tongues of tide-water glaciers is fundamental for understanding dynamics of atmospheric and water masses...
CNR@People
2018, Conference proceedings
An Advanced Guidance & Control System for an Unmanned Vessel with Azimuthal Thrusters
Bibuli M., Bruzzone Ga., Bruzzone Gi., Caccia M., Camporeale G., Chiarella D., Ferretti R., Giacopelli M., Odetti A., Ranieri A., Spirandelli E., Zereik E.
The proposed paper presents the design and development of the combined guidance & control strategies for the autonomous navigation of an unmanned vessel characterized by azimuth-based thrust architect...
CNR@People
2018, Conference posters
Water-air Column Characterisation in Arctic Region using Unmanned Vehicles
Roberta Ferretti, Massimo Caccia, Angelo Odetti, Andrea Ranieri, Federico Carotenuto, Alessandro Zaldei, Angelo Pietro Viola, Gabriele Bruzzone
Monitoring the Arctic regions allows understanding the impact of global warming on Earth's climate but some processes affecting the climate change cannot be fully discerned because data are sparse and...
CNR@People | Link
2017, Conference proceedings
Machine learning methods for acoustic-based automatic Posidonia meadows detection by means of unmanned marine vehicles
Ferretti Roberta, Bibuli Marco, Caccia Massimo, Chiarella Davide, Odetti Angelo, Ranieri Andrea, Zereik Enrica and Bruzzone Gabriele
This work describes the exploitation of a Remotely Operated Vehicle (ROV), equipped with a multi-parametric sensors package (acoustic and video), for the exploration and characterisation of sea-bottom...
CNR@People | DOI: 10.1109/OCEANSE.2017.8084721
2017, Conference proceedings
Towards Posidonia Meadows Detection, Mapping and Automatic recognition using Unmanned Marine Vehicles
Roberta Ferretti, Marco Bibuli, Massimo Caccia, Davide Chiarella, Angelo Odetti, Andrea Ranieri, Enrica Zereik, Gabriele Bruzzone
This paper reports the development of a new methodology for automatic detection and mapping of underwater vegetation by means of highly autonomous marine robotic platforms. In particular, the work des...
CNR@People | DOI: 10.1016/j.ifacol.2017.08.2504
Monitoraggio dello stato del manto stradale usando tecniche di deep learning
Andrea Ranieri, Silvia Biasotti, Elia Moscoso Thompson, Michela Spagnuolo
Questo documento riassume il contributo IMATIallo sviluppo di metodi per il riconoscimento di ammaloramentidel manto stradale, quali buche, crepe,cedimenti attraverso tecniche di deep learning. Talico...
CNR@People | Link
2021, Conference proceedings
Automatic segmentation of archaeological fragments with relief patterns using convolutional neural networks
E. Moscoso Thompson, A. Ranieri, S. Biasotti
The recent commodification of high-quality 3D scanners is leading to the possibility of capturing models of archaeological findsand automatically recognizing their surface reliefs. We present our adva...
CNR@People | DOI: 10.2312/gch.20211411
2020, Conference proceedings
3D dynamic hand gestures recognition using the leap motion sensor and convolutional neural networks
K. Lupinetti, A. Ranieri, F. Giannini, M. Monti
Defining methods for the automatic understanding of gestures is of paramount importance in many application contexts and in Virtual Reality applications for creating more natural and easy-to-use human...
CNR@People | DOI: 10.1007/978-3-030-58465-8_31
2020, Conference proceedings
Are you (Google) Home? Detecting Users Presence through Traffic Analysis of Smart Speakers
D. Caputo, L. Verderame, A. Merlo, A. Ranieri and L. Caviglione
Smart speakers and voice-based virtual assistants are core building blocks of modern smart homes. For instance, they are used to retrieve information, interact with other devices, and command a variet...
CNR@People | Link
2019, Conference posters
Marine robotics for sampling air-sea-ice interface in the Arctic region
Massimo Caccia, Roberta Ferretti, Angelo Odetti, Andrea Ranieri, Giorgio Bruzzone, Edoardo Spirandelli, and Gabriele Bruzzone
Although chemical-physical characterization of air and water columns in the proximity of fronts/tongues of tide-water glaciers is fundamental for understanding dynamics of atmospheric and water masses...
CNR@People
2018, Conference proceedings
An Advanced Guidance & Control System for an Unmanned Vessel with Azimuthal Thrusters
Bibuli M., Bruzzone Ga., Bruzzone Gi., Caccia M., Camporeale G., Chiarella D., Ferretti R., Giacopelli M., Odetti A., Ranieri A., Spirandelli E., Zereik E.
The proposed paper presents the design and development of the combined guidance & control strategies for the autonomous navigation of an unmanned vessel characterized by azimuth-based thrust architect...
CNR@People
2018, Conference posters
Water-air Column Characterisation in Arctic Region using Unmanned Vehicles
Roberta Ferretti, Massimo Caccia, Angelo Odetti, Andrea Ranieri, Federico Carotenuto, Alessandro Zaldei, Angelo Pietro Viola, Gabriele Bruzzone
Monitoring the Arctic regions allows understanding the impact of global warming on Earth's climate but some processes affecting the climate change cannot be fully discerned because data are sparse and...
CNR@People | Link
2017, Conference proceedings
Machine learning methods for acoustic-based automatic Posidonia meadows detection by means of unmanned marine vehicles
Ferretti Roberta, Bibuli Marco, Caccia Massimo, Chiarella Davide, Odetti Angelo, Ranieri Andrea, Zereik Enrica and Bruzzone Gabriele
This work describes the exploitation of a Remotely Operated Vehicle (ROV), equipped with a multi-parametric sensors package (acoustic and video), for the exploration and characterisation of sea-bottom...
CNR@People | DOI: 10.1109/OCEANSE.2017.8084721
2017, Conference proceedings
Towards Posidonia Meadows Detection, Mapping and Automatic recognition using Unmanned Marine Vehicles
Roberta Ferretti, Marco Bibuli, Massimo Caccia, Davide Chiarella, Angelo Odetti, Andrea Ranieri, Enrica Zereik, Gabriele Bruzzone
This paper reports the development of a new methodology for automatic detection and mapping of underwater vegetation by means of highly autonomous marine robotic platforms. In particular, the work des...
CNR@People | DOI: 10.1016/j.ifacol.2017.08.2504
