Deep neural network-based classifiers are prone to errors when processing adversarial examples (AEs). AEs are minimally perturbed input data undetectable to humans posing significant risks to security-dependent applications. Hence. extensive research has been undertaken to develop defense mechanisms that mitigate their threats. https://www.marketingjeunesse.com/product-category/color-treatment/
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