Abstract: Deep learning models are highly susceptible to adversarial attacks, where subtle perturbations in the input images lead to misclassifications. Adversarial examples typically distort specific ...

Abstract: In conventional educational environments, it is labor-intensive, subjective, and susceptible to human error to hand-mark descriptive answers. This article ...