DICKSON-CHARGE-PUMP-BASED VOLTAGE-TO-TIME CONVERSION FOR TIME-BASED ADCS IN 28-NM CMOS




Rectifying Adversarial Examples Using Their Vulnerabilities

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.Most existing methods p

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