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
Автор: Mong-Fong Horng, Hsu-Yang Kung
Издательство: Mdpi AG
Год: 2020
Страниц: 274
Язык: английский
Формат: pdf (true)
Размер: 33.7 MB
Machine Learning (ML) and Deep Learning (DL) techniques have been the crucial tools when it comes to the feature extracting and event estimating for developing applications in the electronics industries. Some techniques have been implemented in the embedded systems and applied to industry 4.0 applications, industrial electronics applications, consumer electronics applications, and other electronics applications. For instance, supervised learning techniques, including neural networks (NN), convolutional neural networks (CNN), and recurrent neural networks (RNN), can be adopted for prediction applications and classification applications in the electronics industries.