Deep Learning

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. 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 is an … 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