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ORCIDFabrizio De Vita
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2020 – today
- 2024
[c13]Rawan M. A. Nawaiseh, Fabrizio De Vita, Enrico Catalfamo, Dario Bruneo:
Leveraging Homeostatic Plasticity to Enable Anomaly Detection in Spiking Neural Networks. SMARTCOMP 2024: 190-197- [c12]Emanuele Giuseppe Siani, Laura Scigliano, Dario Bruneo, Fabrizio De Vita, Valeria Tomaselli
, Danilo Pau:
A Numerical Comparison of Deeply Quantized Models for sEMG Hand Gesture Classification on Constrained Devices. SMARTCOMP 2024: 374-379 - 2023
- [j9]Francesco Vitale, Fabrizio De Vita, Nicola Mazzocca, Dario Bruneo:
A Process Mining-based unsupervised Anomaly Detection technique for the Industrial Internet of Things. Internet Things 24: 100993 (2023) - [j8]Fabrizio De Vita, Giorgio Nocera, Dario Bruneo, Sajal K. Das:
A Novel Echo State Network Autoencoder for Anomaly Detection in Industrial IoT Systems. IEEE Trans. Ind. Informatics 19(8): 8985-8994 (2023) - [c11]Fabrizio De Vita, Rawan M. A. Nawaiseh, Dario Bruneo, Valeria Tomaselli, Marco Lattuada, Mirko Falchetto:
µ-FF: On-Device Forward-Forward Training Algorithm for Microcontrollers. SMARTCOMP 2023: 49-56 - 2022
- [j7]Federico Concone, Fabrizio De Vita, Ajay Pratap, Dario Bruneo, Giuseppe Lo Re, Sajal K. Das:
A fog-assisted system to defend against Sybils in vehicular crowdsourcing. Pervasive Mob. Comput. 83: 101612 (2022) - [j6]Dario Bruneo, Fabrizio De Vita:
Detecting Faults at the Edge via Sensor Data Fusion Echo State Networks. Sensors 22(8): 2858 (2022) - [c10]Fabrizio De Vita, Giorgio Nocera, Orlando Marco Belcore, Antonio Polimeni, Francesco Longo, Dario Bruneo, Massimo Di Gangi:
Traffic Condition Estimation at the Smart City Edge using Deep Learning: A Ro-Pax Terminal Case Study. ISC2 2022: 1-7 - [c9]Fabrizio De Vita, Giorgio Nocera, Dario Bruneo, Valeria Tomaselli, Mirko Falchetto:
On-Device Training of Deep Learning Models on Edge Microcontrollers. iThings/GreenCom/CPSCom/SmartData/Cybermatics 2022: 62-69 - 2021
- [j5]Fabrizio De Vita, Giorgio Nocera, Dario Bruneo, Valeria Tomaselli, Davide Giacalone, Sajal K. Das:
Porting deep neural networks on the edge via dynamic K-means compression: A case study of plant disease detection. Pervasive Mob. Comput. 75: 101437 (2021) - [c8]Fabrizio De Vita, Dario Bruneo, Sajal K. Das:
A Semi-Supervised Bayesian Anomaly Detection Technique for Diagnosing Faults in Industrial IoT Systems. SMARTCOMP 2021: 31-38 - [c7]Federico Concone, Fabrizio De Vita, Ajay Pratap, Dario Bruneo, Giuseppe Lo Re, Sajal K. Das:
A Novel Recruitment Policy to Defend against Sybils in Vehicular Crowdsourcing. SMARTCOMP 2021: 105-112 - [c6]Fabrizio De Vita, Giuseppe Sollazzo, Dario Bruneo, Orazio Pellegrino, Gaetano Bosurgi:
A Cloud Platform for Collecting and Processing Road Pavement Multi Sensor Data. SMARTCOMP 2021: 353-358 - 2020
- [j4]Giovanni Cicceri, Fabrizio De Vita, Dario Bruneo, Giovanni Merlino, Antonio Puliafito:
A deep learning approach for pressure ulcer prevention using wearable computing. Hum. centric Comput. Inf. Sci. 10: 5 (2020) - [j3]Fabrizio De Vita, Dario Bruneo:
Leveraging Stack4Things for Federated Learning in Intelligent Cyber Physical Systems. J. Sens. Actuator Networks 9(4): 59 (2020) - [j2]Fabrizio De Vita, Dario Bruneo, Sajal K. Das:
On the use of a full stack hardware/software infrastructure for sensor data fusion and fault prediction in industry 4.0. Pattern Recognit. Lett. 138: 30-37 (2020) - [c5]Fabrizio De Vita, Dario Bruneo, Sajal K. Das:
A Novel Data Collection Framework for Telemetry and Anomaly Detection in Industrial IoT Systems. IoTDI 2020: 245-251 - [c4]Fabrizio De Vita, Giorgio Nocera, Dario Bruneo, Valeria Tomaselli, Davide Giacalone, Sajal K. Das:
Quantitative Analysis of Deep Leaf: a Plant Disease Detector on the Smart Edge. SMARTCOMP 2020: 49-56
2010 – 2019
- 2019
- [j1]Fabrizio De Vita, Giovanni Nardini, Antonio Virdis, Dario Bruneo, Antonio Puliafito, Giovanni Stea:
Using Deep Reinforcement Learning for Application Relocation in Multi-Access Edge Computing. IEEE Commun. Stand. Mag. 3(3): 71-78 (2019) - [c3]Dario Bruneo, Fabrizio De Vita:
On the Use of LSTM Networks for Predictive Maintenance in Smart Industries. SMARTCOMP 2019: 241-248 - 2018
- [c2]Fabrizio De Vita, Dario Bruneo, Antonio Puliafito, Giovanni Nardini, Antonio Virdis, Giovanni Stea:
A Deep Reinforcement Learning Approach For Data Migration in Multi-Access Edge Computing. Kaleidoscope 2018: 1-8 - [c1]Fabrizio De Vita, Dario Bruneo:
A Deep Learning Approach for Indoor User Localization in Smart Environments. SMARTCOMP 2018: 89-96
Coauthor Index
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