PadNet: Defending Neural Networks Against Adversarial Examples

PadNet is a defense method designed to protect neural networks (AI models that learn patterns from data) against adversarial examples (specially crafted inputs that trick AI systems into making wrong predictions). The paper, published in an academic journal, presents techniques to make these AI systems more robust when facing such attacks.