The Impact of Deep Learning on Advanced Manufacturing Technologies in the USA

Authors

  • Dr. Jean-Pierre Berger Associate Professor of Artificial Intelligence, Université Claude Bernard Lyon 1, France Author

Keywords:

Manufacturing Technologies

Abstract

Deep Learning (DL) models best describe a class of models and algorithms based on deep artificial neural networks (ANN). Over the past decade, ANN models thought to eliminate the ‘AI winter’ years of stagnation in the field have seen a revival spurred by larger data sets, improved computational systems, and ANN optimization breakthroughs leading to state-of-the-art results in a growing number of domains. Models such as deep belief networks (DBN), convolutional neural networks (CNN), re-current neural networks (RNN), long short-term memory (LSTM), and deep Boltzmann machines (DBM) are widely known deep architectures [2].

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Published

2024-09-02

How to Cite

[1]
Dr. Jean-Pierre Berger, “The Impact of Deep Learning on Advanced Manufacturing Technologies in the USA”, J. of Artificial Int. Research and App., vol. 4, no. 2, pp. 215–231, Sep. 2024, Accessed: Oct. 16, 2024. [Online]. Available: https://aimlstudies.co.uk/index.php/jaira/article/view/240

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