Cinzia Giannetti
Orcid: 0000-0003-0339-5872
According to our database1,
Cinzia Giannetti
authored at least 21 papers
between 2013 and 2024.
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Bibliography
2024
Dataset, July, 2024
Leveraging Machine Learning Insights at the Hot Strip Rolling Mill, Tata Steel, Port Talbot.
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2024
2023
A Tool to Combine Expert Knowledge and Machine Learning for Defect Detection and Root Cause Analysis in a Hot Strip Mill.
SN Comput. Sci., September, 2023
A Hybrid Modelling Approach Based on Deep Learning for the Prediction of the Silicon Content in the Blast Furnace.
Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 27th International Conference KES-2023, 2023
2022
Comparison of a Bat and Genetic Algorithm Generated Sequence Against Lead Through Programming When Assembling a PCB Using a Six-Axis Robot With Multiple Motions and Speeds.
IEEE Trans. Ind. Informatics, 2022
Robotics Comput. Integr. Manuf., 2022
Towards scalable and reusable predictive models for cyber twins in manufacturing systems.
J. Intell. Manuf., 2022
Data modelling and Remaining Useful Life estimation of rolls in a steel making cold rolling process.
Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 26th International Conference KES-2022, 2022
Proceedings of the 3rd International Conference on Innovative Intelligent Industrial Production and Logistics, 2022
2021
Making Green Transport a Reality: A Classification Based Data Analysis Method to Identify Properties Suitable for Electric Vehicle Charging Point Installation.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021
A Novel Deep Learning Power Quality Disturbance Classification Method using Autoencoders.
Proceedings of the 13th International Conference on Agents and Artificial Intelligence, 2021
2020
A Deep Learning Model for Smart Manufacturing Using Convolutional LSTM Neural Network Autoencoders.
IEEE Trans. Ind. Informatics, 2020
2019
Cogn. Comput. Syst., 2019
A Deep Learning Framework for Univariate Time Series Prediction Using Convolutional LSTM Stacked Autoencoders.
Proceedings of the IEEE International Symposium on INnovations in Intelligent SysTems and Applications, 2019
A Scalable Deep Convolutional LSTM Neural Network for Large-Scale Urban Traffic Flow Prediction using Recurrence Plots.
Proceedings of the 2019 IEEE AFRICON, Accra, Ghana, September 25-27, 2019, 2019
2017
A framework for improving process robustness with quantification of uncertainties in Industry 4.0.
Proceedings of the IEEE International Conference on INnovations in Intelligent SysTems and Applications, 2017
2016
Comput. Ind. Eng., 2016
Risk based uncertainty quantification to improve robustness of manufacturing operations.
Comput. Ind. Eng., 2016
2015
Organisational Knowledge Management for Defect Reduction and Sustainable Development in Foundries.
Int. J. Knowl. Syst. Sci., 2015
2014
A novel variable selection approach based on co-linearity index to discover optimal process settings by analysing mixed data.
Comput. Ind. Eng., 2014
2013
A coupled penalty matrix approach and principal component based co-linearity index technique to discover product specific foundry process knowledge from in-process data in order to reduce defects.
Comput. Ind., 2013