C. Giannetti

发表

Machine Learning as a universal tool for quantitative investigations of phase transitions

C. Giannetti, B. Lucini, Davide Vadacchino, 2018, Nuclear Physics B.

A quality correlation algorithm for tolerance synthesis and optimization in manufacturing operations

M. R. Ransing, Raed S. Batbooti, C. Giannetti, 2015 .

A robust design of an innovative shaped rebar system using a novel uncertainty model

M. Friswell, J. Sienz, C. Giannetti, 2018, Structural and Multidisciplinary Optimization.

A framework for improving process robustness with quantification of uncertainties in Industry 4.0

Cinzia Giannetti, C. Giannetti, 2017, 2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA).

Colorimetric sensor for pH monitoring of liquid samples using bubble wrap and mobile phone camera

Isabel Wagner, H. Shakeel, S. Fairclough, 2020, 2020 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS).

Optimisation of the Filament Winding Approach Using a Newly Developed In-House Uncertainty Model

Michael I. Friswell, Johann Sienz, Cinzia Giannetti, 2020, Eng.

A robust design of an innovative shaped rebar system using a novel uncertainty model

Michael I. Friswell, Johann Sienz, Cinzia Giannetti, 2018, Structural and Multidisciplinary Optimization.

Knowledge management and knowledge discovery for process improvement and sustainable manufacturing: a foundry case study

Rajesh Ransing, Meghana R. Ransing, David T. Gethin, 2016 .

Organisational Knowledge Management for Defect Reduction and Sustainable Development in Foundries

Meghana R. Ransing, David T. Gethin, Johann Sienz, 2015, Int. J. Knowl. Syst. Sci..

A novel variable selection approach based on co-linearity index to discover optimal process settings by analysing mixed data

Meghana R. Ransing, David T. Gethin, Johann Sienz, 2014, Comput. Ind. Eng..

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

Meghana R. Ransing, Rajesh S. Ransing, Cinzia Giannetti, 2013, Comput. Ind..

KSPMI: A Knowledge-based System for Predictive Maintenance in Industry 4.0

Cecilia Zanni-Merk, François de Bertrand de Beuvron, Qiushi Cao, 2022, Robotics Comput. Integr. Manuf..

A Deep Learning Model for Smart Manufacturing Using Convolutional LSTM Neural Network Autoencoders

Aniekan Essien, Cinzia Giannetti, Aniekan Essien, 2020, IEEE Transactions on Industrial Informatics.

A Robust Vehicle Detection Model for LiDAR Sensor Using Simulation Data and Transfer Learning Methods

Xianghua Xie, C. Giannetti, Kayalvizhi Lakshmanan, 2023, AI.

A Novel Deep Learning Power Quality Disturbance Classification Method using Autoencoders

Grazia Todeschini, Cinzia Giannetti, Callum O'Donovan, 2021, ICAART.

Motion optimisation for improved cycle time and reduced vibration in robotic assembly of electronic components

Christian Andrew Griffiths, M. P. Cooper, K. T. Andrzejewski, 2019, AIMS Electronics and Electrical Engineering.

Short Term Load Forecasting Using TabNet: A Comparative Study with Traditional State-of-the-Art Regression Models

C. Giannetti, Eugenio Borghini, 2021 .

A Deep Learning Framework for Univariate Time Series Prediction Using Convolutional LSTM Stacked Autoencoders

Cinzia Giannetti, Aniekan Essien, Aniekan Essien, 2019, 2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA).

Data-Driven Energy Storage Scheduling to Minimise Peak Demand on Distribution Systems with PV Generation

Grazia Todeschini, Cinzia Giannetti, Eugenio Borghini, 2021 .

Ladle pouring process parameter and quality estimation using Mask R-CNN and contrast-limited adaptive histogram equalisation

C. Giannetti, Ivan Popov, Callum O’Donovan, 2023, The International Journal of Advanced Manufacturing Technology.

A quality correlation algorithm for tolerance synthesis in manufacturing operations

Meghana R. Ransing, Rajesh S. Ransing, Cinzia Giannetti, 2016, Comput. Ind. Eng..

Risk based uncertainty quantification to improve robustness of manufacturing operations

Rajesh S. Ransing, Cinzia Giannetti, C. Giannetti, 2016, Comput. Ind. Eng..

Anomaly Detection of DC Nut Runner Processes in Engine Assembly

C. Giannetti, J. Flynn, Hessel Van Dijk, 2023, AI.

Towards scalable and reusable predictive models for cyber twins in manufacturing systems

Cinzia Giannetti, Aniekan Essien, Aniekan Essien, 2021, Journal of Intelligent Manufacturing.

Segmentation and generalisation for writing skills transfer from humans to robots

Chunxu Li, Cinzia Giannetti, Chenguang Yang, 2019, Cogn. Comput. Syst..

Steelmaking Predictive Analytics Based on Random Forest and Semantic Reasoning

C. Giannetti, Kayalvizhi Lakshmanan, Sadeer Beden, 2023, Applied Sciences.

A Scalable Deep Convolutional LSTM Neural Network for Large-Scale Urban Traffic Flow Prediction using Recurrence Plots

Aniekan E. Essien, Godwin Chukwkelu, Cinzia Giannetti, 2019, 2019 IEEE AFRICON.

Making Green Transport a Reality: A Classification Based Data Analysis Method to Identify Properties Suitable for Electric Vehicle Charging Point Installation

J. Flynn, C. Giannetti, E. Brealy, 2021, 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS.

Using Convolutional Neural Networks to Map Houses Suitable for Electric Vehicle Home Charging

Cinzia Giannetti, James Flynn, J. Flynn, 2021, AI.

Pre-Trained CNN for Classification of Time Series Images of Anti-Necking Control in a Hot Strip Mill

C. Giannetti, S. Latham, 2021, The Proceedings of The 9th IIAE International Conference on Industrial Application Engineering 2020.