NIST · ИТ · e974a8deed33815f1fa0
Towards Generative Adversarial Network on Industrial Internet of Things
Machine learning, as a viable way of conducting data analytics, has been successfully applied to a number of areas. Nonetheless, the lack of sufficient data is one critical issue for applying machine learning in Industrial Internet of Things (IIoT) systems
NIST · ИТОфициальный источник · 2022-10-01
{
"title_en": "Towards Generative Adversarial Network on Industrial Internet of Things",
"designation": "",
"series": "",
"status": "",
"date": "2022-10-01",
"date_original": "October 1, 2022",
"url": "https://www.nist.gov/publications/towards-generative-adversarial-network-industrial-internet-things",
"source": "NIST Publications",
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"authors_en": "Cheng Qian , Wei Yu , Chao Lu, David W. Griffith , Nada T. Golmie",
"abstract_excerpt_en": "Machine learning, as a viable way of conducting data analytics, has been successfully applied to a number of areas. Nonetheless, the lack of sufficient data is one critical issue for applying machine learning in Industrial Internet of Things (IIoT) systems",
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{
"title_en": "Towards Generative Adversarial Network on Industrial Internet of Things",
"designation": "",
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"date": "2022-10-01",
"date_original": "October 1, 2022",
"url": "https://www.nist.gov/publications/towards-generative-adversarial-network-industrial-internet-things",
"source": "NIST Publications",
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"authors_en": "Cheng Qian , Wei Yu , Chao Lu, David W. Griffith , Nada T. Golmie",
"abstract_excerpt_en": "Machine learning, as a viable way of conducting data analytics, has been successfully applied to a number of areas. Nonetheless, the lack of sufficient data is one critical issue for applying machine learning in Industrial Internet of Things (IIoT) systems"
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