565 citations · 896 across the 20 of their papers we have counts for
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cs.LG2021
Tool- and Domain-Agnostic Parameterization of Style Transfer Effects Leveraging Pretrained Perceptual Metrics
Hiromu Yakura, Yuki Koyama, Masataka Goto
Current deep learning techniques for style transfer would not be optimal for design support since their "one-shot" transfer does not fit exploratory design processes. To overcome t…
cs.LG2019
Generate (non-software) Bugs to Fool Classifiers
Hiromu Yakura, Youhei Akimoto, Jun Sakuma
In adversarial attacks intended to confound deep learning models, most studies have focused on limiting the magnitude of the modification so that humans do not notice the attack. O…
cs.LG2018★ 173 cited
Robust Audio Adversarial Example for a Physical Attack
Hiromu Yakura, Jun Sakuma
We propose a method to generate audio adversarial examples that can attack a state-of-the-art speech recognition model in the physical world. Previous work assumes that generated a…