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.roneverhart.com/Bowling-Pin-Shaped-Acrylic-Candy-Boxes-24-Pack-1-29-X4-13/
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