Jana Poľašková

Analysis of adversarial examples in neural network image classifiers

This work explores different neural network architectures, including fully connected networks, classical convolutional networks, and residual networks, under four types of adversarial attacks constrained by different L p norms, and investigates how adversarial examples affect the internal representations of networks by analyzing the nearest neighbors and class manifold proximity across layers.