Abstract. Effective anomaly detection can reduce the electricity consumption and carbon emissions in aluminium extrusion processes.
Transfer learning for aluminium extrusion electricity consumption ...
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Abstract. Effective anomaly detection can reduce the electricity consumption and carbon emissions in aluminium extrusion processes.
The experimental results show that the proposed approach can identify electricity anomaly events in real time and it is shown that transferring learning ...
Apr 25, 2024 · Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networks. Int. J. Comput. Integr. Manuf ...
Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networks. Int. J. Comput. Integr. Manuf. 31(4-5): 396 ...
Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networks. Int. J. Comput. Integr. Manuf.,. 31(4-5):396 ...
Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networks ... electricity consumption anomaly detection ...
Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networks. International Journal of Computer Integrated ...
Jan 13, 2024 · We discuss the challenges and limitations of deep transfer learning in industrial contexts and conclude the survey with practical directions and ...
Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networks. Authors. Peng Liang · ORCID ID · Hai-Dong Yang ...