Search Results for author: Takahiro Kanzaki

Found 1 papers, 0 papers with code

Perceptual Deep Neural Networks: Adversarial Robustness through Input Recreation

no code implementations2 Sep 2020 Danilo Vasconcellos Vargas, Bingli Liao, Takahiro Kanzaki

Thus, $\varphi$DNNs reveal that input recreation has strong benefits for artificial neural networks similar to biological ones, shedding light into the importance of purposely corrupting the input as well as pioneering an area of perception models based on GANs and autoencoders for robust recognition in artificial intelligence.

Adversarial Robustness Super-Resolution

Cannot find the paper you are looking for? You can Submit a new open access paper.