Understand
Recent studies have shown that Convolutional Neural Networks (CNNs) are vulnerable to a small perturbation of input called "adversarial examples".
- In this work, we propose a new feedforward CNN that improves robustness in the presence of adversarial noise.
- Our model uses stochastic additive noise added to the input image and to the CNN models.
- The proposed model operates in conjunction with a CNN trained with either standard or adversarial objective function.
Reading the bibliography…