Style transfer for CNC machine input data preprocessing
Advances in deep neural networks have led to impressive results in recent years. The new technologies such as cross-domain adaptation, reinforcement learning and generative adversarial networks have shown a real promise for industrial and real-life applications. In this paper, the results of the exp...
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| 主要な著者: | , , , |
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| フォーマット: | Статья |
| 言語: | English |
| 出版事項: |
Institute of Physics Publishing
2019
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| 主題: | |
| オンライン･アクセス: | https://www.scopus.com/record/display.uri?eid=2-s2.0-85076353555&origin=resultslist&sort=plf-f&src=s&st1=Style+Transfer+for+CNC+Machine+Input+Data+Preprocessing&st2=&sid=d26f2c404dd20f2650d6d115a369a105&sot=b&sdt=b&sl=70&s=TITLE-ABS-KEY%28Style+Transfer+for+CNC+Machine+Input+Data+Preprocessing%29&relpos=0&citeCnt=0&searchTerm= https://dspace.ncfu.ru/handle/20.500.12258/10144 |
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https://www.scopus.com/record/display.uri?eid=2-s2.0-85076353555&origin=resultslist&sort=plf-f&src=s&st1=Style+Transfer+for+CNC+Machine+Input+Data+Preprocessing&st2=&sid=d26f2c404dd20f2650d6d115a369a105&sot=b&sdt=b&sl=70&s=TITLE-ABS-KEY%28Style+Transfer+for+CNC+Machine+Input+Data+Preprocessing%29&relpos=0&citeCnt=0&searchTerm=https://dspace.ncfu.ru/handle/20.500.12258/10144