… They designed a robust adversarial perturbation which gets better generalization ability.
It is hard to detect an attack that applies a slight disturbance to the original object. Therefore, …

… this kind perturbation to attack deep proposal-based object … deep proposal-based models
without knowing the details of … other models and perturbations crafted by robust model have …

… various object detectors covering proposal-based and regression-… the robustness of proposed
methods towards adversarial … Threat of adversarial attacks on deep learning in computer …

… We further develop an adversarial training approach which … of deep learning models is
their issues with robustness. It … of the model using the perturbed images as typically done in …

… to enhance the robustness of the deep learning models, and … Finally, we add the class-wise
adversarial perturbations into … on attacking the object proposal-based detector have two …

… classification models, thereby declaring deep learning models… The first attack is an adversarial
perturbation based Blackbox … learning models are more robust than adversarial examples …

… Deep convolutional neural networks are widely witnessed vul… of adversarial perturbations
across different detection networks. Li et al. [14] proposed a robust adversarial perturbation (…

… similar accuracy as proposal based models while processing … model, our final robust
spatially constrained perturbation is … robust physical adversarial objects against current recogni…

… show examples of perturbations and adversarial examples generated by our attacks on
four different STD models (ie… Lyu et al., “Robust adversarial perturbation on deep proposal-based …

… , which means that DAG is based on the proposal-based OD methods [38]. It finds out …
adversarial perturbations and quantify and compare the robustness of machine learning models…