Robustness Analysis of Deep Neural Networks in the Presence of Adversarial Perturbations and Noisy Labels

··· lezzter Preis 38.27€ ··· 9783863598020 ··· 1036178900 ···
In this thesis, we study the robustness and generalization properties of Deep Neural Networks (DNNs) under various noisy regimes, due to corrupted inputs or labels. Such corruptions can be either random or intentionally crafted to disturb the target DNN. Inputs corrupted by maliciously designed perturbations are known as adversarial examples and have been shown to severely degrade the performance of DNNs. However, due to the non-linearity of DNNs, crafting such perturbations is non-trivial. [...]
Hersteller: Apprimus Wissenschaftsver
Marke: Apprimus Wissenschaftsver
EAN: 9783863598020
Kat: Hardcover/Naturwissenschaften, Medizin, Informatik, Technik/Technik/Maschinenbau, Fertigungstechnik
Lieferzeit: Sofort lieferbar
Versandkosten: Ab 20¤ Versandkostenfrei in Deutschland
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7: Robustness Analysis of Deep Neural Networks in the Presence of Adversarial Perturbations and Noisy Labels
:::: Hardcover/Naturwissenschaften, Medizin, Informatik, Technik/Technik/Maschinenbau, Fertigungstechnik

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: Robustness : Analysis : Neural : Networks : Presence : Adversarial : Perturbations : Labels :

Robustness Analysis of Deep Neural Networks in the Presence of Adversarial Perturbations and Noisy Labels

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