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References from Steel rolling in the age of artificial intelligence: a review. Local targets link to admitted publications; unresolved targets remain external evidence.
Prediction of tandem cold-rolled strip flatness based on Attention-LSTM model
10.1016/j.jmapro.2023.02.048 · 2023 · External reference
Foundation models for multimodal image data fusion in materials science
10.3389/fmats.2026.1815017 · 2026 · External reference
Hybrid model of mathematical and neural network formulations for rolling force and temperature prediction in hot rolling processes
10.1109/access.2020.3016725 · 2020 · External reference
Influence of transverse property differences in hot-rolled high-strength strip on cold rolling deformation behavior
10.1007/s00170-025-15643-3 · 2025 · External reference
Interpretable machine learning modeling of alloy composition-process-property relationships based on industrial big data in hot strip rolling
10.1016/j.jmapro.2025.06.059 · 2025 · External reference
Surface defects of rolled metal products recognised by a deep neural network under different illuminance levels and low-amplitude vibration
10.1007/s00170-025-15942-9 · 2025 · External reference
Advanced technology of combined thin slab continuous casting and steel strip hot rolling
10.1007/s11015-019-00747-5 · 2019 · External reference
The assessment list for trustworthy artificial intelligence, A review and recommendations
10.3389/frai.2023.1020592 · 2023 · External reference
Optimization of work roll bending model in unsteady process of tandem cold rolling based on CF-PSO-SVM
2021 · External reference
Assessing the ethical and social concerns of artificial intelligence in neuroinformatics research, an empirical test of the European Union assessment list for trustworthy AI (ALTAI), AI and ethics 3, 745
10.1007/s43681-022-00201-4 · 2023 · External reference
Modeling and optimization of thick plate rolling force based on mechanism and data
2025 · External reference
Predicting flatness of strip tandem cold rolling using a general regression neural network optimized by differential evolution algorithm
10.1007/s00170-023-11330-3 · 2023 · External reference
Hot rolling in the age of artificial intelligence: towards enhanced efficiency, quality and sustainability in steel industry
10.3389/fmats.2026.1910968 · External reference
Analysis of internal cracks in high carbon casting bloom induced by soft reduction process and its improvement using numerical simulations and industrial experiments
10.1051/metal/2020079 · 2021 · External reference
Comparative studies on a chamfer technology and a convex roll technology During the soft reduction process
10.24425/amm.2021.136386 · 2022 · External reference
Machine learning for tandem cold rolling, exploring innovations, challenges, and industrial applications
10.1007/s00170-025-16652-y · External reference
Machine learning techniques for the comprehensive analysis of the continuous casting processes, slab defects
10.1177/03019233251318492 · External reference
Intelligent empowerment for green steel manufacturing, artificial intelligence-driven process optimization
10.1002/srin.202500737 · External reference
Editorial, digital technology for materials science and processes modelling
10.3389/fmats.2026.1846730 · External reference
Steelmaking in the age of artificial intelligence
10.1007/s40430-026-06465-9 · External reference
Artificial intelligence for smarter steelmaking processes, towards enhanced efficiency, quality and sustainability
10.1007/s12613-026-3445-2 · External reference
Hot rolling in the age of artiffcial intelligence: towards enhanced efffciency, quality and sustainability in steel industry
10.3389/fmats.2026.1910968 · External reference