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  • How does AET work?

  • By estimating random- ly sampled transformations at output end, AET forces the encoder to learn good representations so that they contain suf銉烩€ent information about visual structures of both the original and transformed images.

  • What is Advanced Evasion technique (AET)?

  • An advanced evasion technique (AET) is a type of network attack that combines several different known evasion methods to create a new technique that’s delivered over several layers of the network simultaneously.

  • How are the AET networks trained by SGD?

  • The AET networks are trained by SGD with a batch size of 512original images and their transformed counterparts. Momentum and weight decay are set to 0.9and 5锞冦兓10绔忋兓. The learning rate is initialized to 0.1and scheduled to drop by a factor of 5after 240, 480, 640, 800and 1,000epochs. The model is trained for 1,500epochs in total.

  • What is AET transformation in image processing?

  • For AET- af銉伙冀e, the af銉伙冀e transformation is a composition of a ran- dom rotation with [绔忋兓80绗筹溅,180 ], a random translation by 锞傦奖0.2of image height and width in both vertical and hori- zontal directions, and a random scaling factor of [0.7,1.3], along with a random shearing of [绔忋兓0绗筹溅,30绗筹溅]degree.

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