\begin{equation} x' = x - \epsilon sign(\nabla_x J(\theta, x, l')). \end{equation}\qquad(7) 作者将这种攻击称为单步目标类别方法(One-step Target Class Method, OTCM)。 [84] 发现,由于梯度掩蔽(gradient masking),经过对抗训练的FGSM对白盒攻击比对黑盒攻击更鲁棒。他们提出了一种新的攻击方...
Adversarial examples in the physical world(CVPR 2016):提出BIM方法,即优化时用若干小步代替一大步,进一步提出non-targeted版本,Iterative Least-likely Class Method (ILCM). 作者单位: Google. Jacobian-based Saliency Map Attack (JSMA): The Limitations of Deep Learning in Adversarial Settings(EURO S&P): ...
@lightvector Derived studies based on the LG Cup game record. Here is a diagram of the change if B-B12 is not moved. KataGo_sample_20221203_0001.txt At a stage with very little exploration, a false rating of B-A17 will give a false value of black not bad. If properly adjusted, the...
在MS COCO 2014数据集上测试 6中目标检测算法,2中语义分割算法 1. Introduction 基于深度学习的算法,在计算机视觉领域,获得了非常不错的表现 包括图片分类,目标检测,语义分割 然而,最近研究表明,基于CNN的算法容易受到对抗样本的攻击 人类无法分辨,但可以欺骗分类器 与图片分类不同,语义分割和目标检测上的对抗攻击更加...
L-BFGS)、快速梯度符号法(fast gradient sign method, FGSM)、基本迭代攻击/投影梯度下降(basic iterative attack/projected gradient descent, BIA/PGD)、分布式对抗攻击(distributionally adversarial attack, DAA)、Carlini和Wagner(C&W)攻击、基于雅可比的显著图攻击(Jacobian-based saliency map attack, JSMA)以及DeepFo...
In another study, the author proposed the application of a semisupervised generative adversarial network (GAN)-based method to predict binding affinity. While GAN-based networks were used for feature extraction and a regression network for prediction, this combination was used to learn protein drug ...
[27] proposed another CNN-based method that utilized the enhanced cross-layer cost aggregation and 3D PatchMatch to extract the feature maps to generate face sketch images. Instead of generating the sketch image directly, Jiang et al. [12] put forward the learning of the residual map between ...
Following Eq. (1), we let the model parameter be denoted asθ, model loss asLand training input&label as (x, y). The projected gradient descent (PGD) method repeatedly adjusts the model’s inputs x in the direction of maximizing the loss function, i.e.,sign(∇xL(x, y; θ...
GAN-based(不需要对数据分布做显式假设) CycleGAN-VC,StarGAN-VC 解耦方面:用ASR来提语音中的linguistic features,然后加上speaker信息。这种做法比较依赖于ASR的精度。其他解耦方法包括autoencoder、vector quantization、instance normalization。 3 Method NVC-Net包括一个content encoder Ec,一个speaker encoder Es,一个...
最近的一种防御方法(diffusion-based purification,基于扩散的净化)利用扩散模型来净化输入图像并实现最先进的鲁棒性。根据防御使用的扩散模型的类型,基于扩散的净化可以分为基于分数的净化(使用基于分数的扩散模型)和基于DDPM的净化(去噪扩散概率模型(DDPM))。