DE VITA, Fabrizio

DE VITA, Fabrizio  

Dipartimento di Ingegneria  

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Risultati 1 - 20 di 26 (tempo di esecuzione: 0.051 secondi).
Titolo Data di pubblicazione Autore(i) File
A Cloud Platform for Collecting and Processing Road Pavement Multi Sensor Data 1-gen-2021 De Vita, F.; Sollazzo, G.; Bruneo, D.; Pellegrino, O.; Bosurgi, G.
A deep learning approach for indoor user localization in smart environments 1-gen-2018 De Vita, F.; Bruneo, D.
A deep learning approach for pressure ulcer prevention using wearable computing 1-gen-2020 Cicceri, G.; De Vita, F.; Bruneo, D.; Merlino, G.; Puliafito, A.
A deep reinforcement learning approach for data migration in multi-access edge computing 1-gen-2018 De Vita, F.; Bruneo, D.; Puliafito, A.; Nardini, G.; Virdis, A.; Stea, G.
A fog-assisted system to defend against Sybils in vehicular crowdsourcing 1-gen-2022 Concone, F.; De Vita, F.; Pratap, A.; Bruneo, D.; Lo Re, G.; Das, S. K.
A novel data collection framework for telemetry and anomaly detection in industrial iot systems 1-gen-2020 De Vita, F.; Bruneo, D.; Das, S. K.
A Novel Echo State Network Autoencoder for Anomaly Detection in Industrial IoT Systems 1-gen-2023 De Vita, F.; Nocera, G.; Bruneo, D.; Das, S. K.
A Novel Recruitment Policy to Defend against Sybils in Vehicular Crowdsourcing 1-gen-2021 Concone, F.; De Vita, F.; Pratap, A.; Bruneo, D.; Re, G. L.; Das, S. K.
A Numerical Comparison of Deeply Quantized Models for sEMG Hand Gesture Classification on Constrained Devices 1-gen-2024 Siani, E. G.; Scigliano, L.; Bruneo, D.; De Vita, F.; Tomaselli, V.; Pau, D.
A Process Mining-based unsupervised Anomaly Detection technique for the Industrial Internet of Things 1-gen-2023 Vitale, F.; De Vita, F.; Mazzocca, N.; Bruneo, D.
A Semi-Supervised Bayesian Anomaly Detection Technique for Diagnosing Faults in Industrial IoT Systems 1-gen-2021 De Vita, F.; Bruneo, D.; Das, S. K.
A web platform for the management of road survey and maintenance information: A preliminary step towards smart road management systems 1-gen-2022 Bosurgi, Gaetano; Bruneo, Dario; De Vita, Fabrizio; Pellegrino, Orazio; Sollazzo, Giuseppe
Deep learning techniques for Intelligent Cyber Physical Systems: towards a new generation of smart and autonomous things 28-gen-2021 DE VITA, Fabrizio
Detecting Faults at the Edge via Sensor Data Fusion Echo State Networks 1-gen-2022 Bruneo, D.; De Vita, F.
Innovative smart road management systems in the urban context: Integrating smart sensors and miniaturized sensing systems 1-gen-2022 Praticò, Filippo Giammaria; Bosurgi, Gaetano; Bruneo, Dario; Cafiso, Salvatore; De Vita, Fabrizio; Di Graziano, Alessandro; Fedele, Rosario; Pellegrino, Orazio; Sollazzo, Giuseppe
Leveraging Homeostatic Plasticity to Enable Anomaly Detection in Spiking Neural Networks 1-gen-2024 Nawaiseh, R. M. A.; De Vita, F.; Catalfamo, E.; Bruneo, D.
Leveraging Stack4Things for Federated Learning in Intelligent Cyber Physical Systems 1-gen-2020 De Vita, Fabrizio; Bruneo, Dario
On the use of a full stack hardware/software infrastructure for sensor data fusion and fault prediction in industry 4.0 1-gen-2020 De Vita, F.; Bruneo, D.; Das, S. K.
On the use of LSTM networks for predictive maintenance in smart industries 1-gen-2019 Bruneo, D.; De Vita, F.
On-Device Training of Deep Learning Models on Edge Microcontrollers 1-gen-2022 De Vita, F.; Nocera, G.; Bruneo, D.; Tomaselli, V.; Falchetto, M.