DEEP DETECTOR HEALTH MANAGEMENT UNDER ADVERSARIAL CAMPAIGNS
Machine learning models are vulnerable to adversarial inputs that induce seemingly unjustifiable errors. As automated classifiers are increasingly used in industrial control systems and machinery, these adversarial errors could grow to be a serious problem. Despite numerous studies over the past few...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
The Prognostics and Health Management Society
2019-12-01
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| Series: | International Journal of Prognostics and Health Management |
| Subjects: |