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Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networks. from books.google.com
With the democratization of cyber-physical systems, edge computing, and large-scale data infrastructure, the volume of operational data available is continuously increasing.
Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networks. from books.google.com
This open access book presents the proceedings of the 3rd Indo-German Conference on Sustainability in Engineering held at Birla Institute of Technology and Science, Pilani, India, on September 16–17, 2019.
Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networks. from books.google.com
This book is a comprehensive collection of chapters focusing on the core areas of computing and their further applications in the real world. Each chapter is a paper presented at the Computing Conference 2021 held on 15-16 July 2021.
Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networks. from books.google.com
The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.
Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networks. from books.google.com
This book constitutes the proceedings of the 12th Mexican Conference on Pattern Recognition, MCPR 2020, which was due to be held in Morelia, Mexico, in June 2020. The conference was held virtually due to the COVID-19 pandemic.
Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networks. from books.google.com
This edited volume is targeted at presenting the latest state-of-the-art methodologies in "Hybrid Evolutionary Algorithms".
Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networks. from books.google.com
This book starts with the description of polarization in classical optics, including also a chapter on crystal optics, which is necessary to understand the use of nonlinear crystals.
Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networks. from books.google.com
This two-volume book presents the outcomes of the 8th International Conference on Soft Computing for Problem Solving, SocProS 2018.
Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networks. from books.google.com
Statistical pattern recognition; Probability density estimation; Single-layer networks; The multi-layer perceptron; Radial basis functions; Error functions; Parameter optimization algorithms; Pre-processing and feature extraction; Learning ...