Fabrizio De Vita

According to our database, Fabrizio De Vita authored at least 20 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

A Process Mining-based unsupervised Anomaly Detection technique for the Industrial Internet of Things.

Francesco Vitale, Fabrizio De Vita, Nicola Mazzocca, Dario Bruneo

Internet Things, December, 2023

A Novel Echo State Network Autoencoder for Anomaly Detection in Industrial IoT Systems.

Fabrizio De Vita, Giorgio Nocera, Dario Bruneo, Sajal K. Das

IEEE Trans. Ind. Informatics, August, 2023

µ-FF: On-Device Forward-Forward Training Algorithm for Microcontrollers.

Fabrizio De Vita, Rawan M. A. Nawaiseh, Dario Bruneo, Valeria Tomaselli, Marco Lattuada, Mirko Falchetto

Proceedings of the 2023 IEEE International Conference on Smart Computing, 2023

2022

Detecting Faults at the Edge via Sensor Data Fusion Echo State Networks.

Dario Bruneo, Fabrizio De Vita

Sensors, 2022

A fog-assisted system to defend against Sybils in vehicular crowdsourcing.

Federico Concone, Fabrizio De Vita, Ajay Pratap, Dario Bruneo, Giuseppe Lo Re, Sajal K. Das

Pervasive Mob. Comput., 2022

On-Device Training of Deep Learning Models on Edge Microcontrollers.

Fabrizio De Vita, Giorgio Nocera, Dario Bruneo, Valeria Tomaselli, Mirko Falchetto

Proceedings of the 2022 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, 2022

Traffic Condition Estimation at the Smart City Edge using Deep Learning: A Ro-Pax Terminal Case Study.

Fabrizio De Vita, Giorgio Nocera, Orlando Marco Belcore, Antonio Polimeni, Francesco Longo, Dario Bruneo, Massimo Di Gangi

Proceedings of the IEEE International Smart Cities Conference, 2022

2021

Porting deep neural networks on the edge via dynamic K-means compression: A case study of plant disease detection.

Fabrizio De Vita, Giorgio Nocera, Dario Bruneo, Valeria Tomaselli, Davide Giacalone, Sajal K. Das

Pervasive Mob. Comput., 2021

A Cloud Platform for Collecting and Processing Road Pavement Multi Sensor Data.

Fabrizio De Vita, Giuseppe Sollazzo, Dario Bruneo, Orazio Pellegrino, Gaetano Bosurgi

Proceedings of the IEEE International Conference on Smart Computing, 2021

A Semi-Supervised Bayesian Anomaly Detection Technique for Diagnosing Faults in Industrial IoT Systems.

Fabrizio De Vita, Dario Bruneo, Sajal K. Das

Proceedings of the IEEE International Conference on Smart Computing, 2021

A Novel Recruitment Policy to Defend against Sybils in Vehicular Crowdsourcing.

Federico Concone, Fabrizio De Vita, Ajay Pratap, Dario Bruneo, Giuseppe Lo Re, Sajal K. Das

Proceedings of the IEEE International Conference on Smart Computing, 2021

2020

On the use of a full stack hardware/software infrastructure for sensor data fusion and fault prediction in industry 4.0.

Fabrizio De Vita, Dario Bruneo, Sajal K. Das

Pattern Recognit. Lett., 2020

Leveraging Stack4Things for Federated Learning in Intelligent Cyber Physical Systems.

Fabrizio De Vita, Dario Bruneo

J. Sens. Actuator Networks, 2020

A deep learning approach for pressure ulcer prevention using wearable computing.

Giovanni Cicceri, Fabrizio De Vita, Dario Bruneo, Giovanni Merlino, Antonio Puliafito

Hum. centric Comput. Inf. Sci., 2020

Quantitative Analysis of Deep Leaf: a Plant Disease Detector on the Smart Edge.

Fabrizio De Vita, Giorgio Nocera, Dario Bruneo, Valeria Tomaselli, Davide Giacalone, Sajal K. Das

Proceedings of the IEEE International Conference on Smart Computing, 2020

A Novel Data Collection Framework for Telemetry and Anomaly Detection in Industrial IoT Systems.

Fabrizio De Vita, Dario Bruneo, Sajal K. Das

Proceedings of the Fifth IEEE/ACM International Conference on Internet-of-Things Design and Implementation, 2020

2019

Using Deep Reinforcement Learning for Application Relocation in Multi-Access Edge Computing.

Fabrizio De Vita, Giovanni Nardini, Antonio Virdis, Dario Bruneo, Antonio Puliafito, Giovanni Stea

IEEE Commun. Stand. Mag., 2019

On the Use of LSTM Networks for Predictive Maintenance in Smart Industries.

Dario Bruneo, Fabrizio De Vita

Proceedings of the IEEE International Conference on Smart Computing, 2019

2018

A Deep Learning Approach for Indoor User Localization in Smart Environments.

Fabrizio De Vita, Dario Bruneo

Proceedings of the 2018 IEEE International Conference on Smart Computing, 2018

A Deep Reinforcement Learning Approach For Data Migration in Multi-Access Edge Computing.

Fabrizio De Vita, Dario Bruneo, Antonio Puliafito, Giovanni Nardini, Antonio Virdis, Giovanni Stea

Proceedings of the 2018 ITU Kaleidoscope: Machine Learning for a 5G Future, 2018