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Marco Bindi
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2020 – today
- 2024
- [c9]Matteo Intravaia, Lorenzo Becchi, Marco Bindi
, Luigi Costanzo, Cristian C. Garzon-Alfonso, Vipinkumar Shriram Meshram
Sensitivity analysis of PV produced power in presence of measurement uncertainty. MetroInd4.0 & IoT 2024: 245-250 - [c8]Marco Bindi, Vipinkumar Shriram Meshram, Antonio Luchetta, Lorenzo Becchi, Matteo Intravaia, Alicia Triviño, Eliseo Villagrasa:
Foreign Object Detection for Wireless Power Transfer Systems Using MLMVN. RTSI 2024: 453-458 - [c7]Lorenzo Becchi, Marco Bindi, Cristian Camilo Garzon-Alfonso, Matteo Intravaia, Gabriele Maria Lozito, Francesco Grasso:
A Neural Network Based Control Strategy for Constant Current Battery Chargers with PV Source. RTSI 2024: 459-464 - 2023
- [j12]Andrea Genangeli
A Novel Correction Methodology to Improve the Performance of a Low-Cost Hyperspectral Portable Snapshot Camera. Sensors 23(24): 9685 (2023) - [j11]Marco Bindi
Failure Prevention in DC-DC Converters: Theoretical Approach and Experimental Application on a Zeta Converter. IEEE Trans. Ind. Electron. 70(1): 930-939 (2023) - [c6]Matteo Intravaia, Lorenzo Becchi, Marco Bindi
Autoencoders for Hourly Load Profile Reconstruction in Renewable Energy Communities. EUROCON 2023: 280-285 - [c5]Matteo Intravaia, Marco Bindi
Predictive Maintenance of Actuated Quarter-Turn Valves Using Artificial Intelligence. MetroXRAINE 2023: 149-154 - [c4]Matteo Intravaia, Marco Bindi
Prognostic Analysis of Switching Devices in DC-DC Converters. MetroXRAINE 2023: 224-229 - 2022
- [j10]Marco Bindi
Machine Learning-Based Monitoring of DC-DC Converters in Photovoltaic Applications. Algorithms 15(3): 74 (2022) - [j9]Riccardo Rossi
Implementation of an algorithm for automated phenotyping through plant 3D-modeling: A practical application on the early detection of water stress. Comput. Electron. Agric. 197: 106937 (2022) - [j8]Andrea Genangeli
A Novel Hyperspectral Method to Detect Moldy Core in Apple Fruits. Sensors 22(12): 4479 (2022) - [c3]Marco Bindi
Classification of Power Quality disturbances using Multi-Valued Neural Networks and Convolutional Neural Networks. IJCNN 2022: 1-8 - [c2]Marco Bindi
Applications of Machine Learning Techniques for the Monitoring of Electrical Transmission and Distribution lines. SMACD 2022: 1-4 - [d1]Carlos Iturrino, Marco Bindi, Fabio Corti:
Power Quality Disturbance. IEEE DataPort, 2022 - 2020
- [j7]Riccardo Rossi
Performances Evaluation of a Low-Cost Platform for High-Resolution Plant Phenotyping. Sensors 20(11): 3150 (2020)
2010 – 2019
- 2019
- [c1]Igor N. Aizenberg, Marco Bindi
Testability Analysis in Neural Network Based Fault Diagnosis of DC-DC Converter. RTSI 2019: 265-268 - 2017
- [j6]Balázs Grosz
The implication of input data aggregation on up-scaling soil organic carbon changes. Environ. Model. Softw. 96: 361-377 (2017) - 2016
- [j5]Gang Zhao, Holger Hoffmann, Jagadeesh B. Yeluripati
Evaluating the precision of eight spatial sampling schemes in estimating regional means of simulated yield for two crops. Environ. Model. Softw. 80: 100-112 (2016) - 2015
- [j4]Frank Ewert
Crop modelling for integrated assessment of risk to food production from climate change. Environ. Model. Softw. 72: 287-303 (2015) - [j3]Marco Moriondo
Modelling olive trees and grapevines in a changing climate. Environ. Model. Softw. 72: 387-401 (2015) - [j2]Kurt Christian Kersebaum
Analysis and classification of data sets for calibration and validation of agro-ecosystem models. Environ. Model. Softw. 72: 402-417 (2015) - 2013
- [j1]Lorenzo Brilli
Simulation of olive grove gross primary production by the combination of ground and multi-sensor satellite data. Int. J. Appl. Earth Obs. Geoinformation 23: 29-36 (2013)
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last updated on 2024-12-13 19:14 CET by the dblp team
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