Enhancing adversarial attacks with resize-invariant and logical ensemble.

In black-box scenarios, most transfer-based attacks usually improve the transferability of adversarial examples by optimizing the gradient calculation of the input image. Unfortunately, since the gradient information is only calculated and optimized for each pixel point in the image individually, the generated adversarial examples tend to overfit the local model and have poor transferability to the target model. To tackle the issue, we propose a resize-invariant method (RIM) and a logical ensemble transformation method (LETM) to enhance the transferability of adversarial examples.

Carbonized polyaniline bridging nanodiamond-graphene hybrids for enhanced microwave absorptions with ultrathin thickness.

For conventional design of the electromagnetic absorption materials, introduction of magnetic materials into dielectric materials has been found to achieve better impedance matching, but lead to increase in weight and decrease in chemical stability, therefore limiting their practical applications. In this work, metal-free electromagnetic coupling was achieved by the design of nitrogen-doped nanodiamond/graphene hybrids. Polyaniline is used to self-assembled bridge the nanodiamond and graphene, and the carbonization is carried out for construction and regulation of the C•••N polarization and nitrogen doping.