Deep Learning

The advent of the deep learning evolutionary algorithm EvoDN2 and its recent applications

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The advent of the deep learning evolutionary algorithm EvoDN2 and its recent applications Nirupam Chakraborti Faculty of Mechanical Engineering, Czech Technical University in Prague, Czech Republic. DOI: https://doi.org/10.7494/cmms.2025.2.1021 Abstract: The evolutionary deep learning algorithm EvoDN2 is an emerging strategy for data-driven intelligent learning and many-objective optimisation capable of handling a large volume of noisy and … Read more

An evaluation of the capabilities of image-based metal component defect recognition with deep learning techniques

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An evaluation of the capabilities of image-based metal component defect recognition with deep learning techniques Michał P. Wójcik*, Kacper Pawlikowski, Łukasz Madej AGH University of Krakow, Mickiewicza 30, 30-059 Krakow, Poland. *corresponding author DOI: https://doi.org/10.7494/cmms.2024.3.0839 Abstract: In the era of Industry 4.0, deploying highly specialised machine learning models trained on unique and often scarce datasets … Read more

Evolutionary data driven modelling and many objective optimization of non linear noisy data in the blast furnace iron making process

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Evolutionary data driven modelling and many objective optimization of non linear noisy data in the blast furnace iron making process Bashista Kumar Mahanta, Nirupam Chakraborti Department of Metallurgical and Materials Engineering Indian Institute of Technology, Kharagpur, India. DOI: https://doi.org/10.7494/cmms.2021.3.0733 Abstract: Optimization of process parameters in modern blast furnace operation, where both control and accessing large … Read more