Results 81 to 90 of about 173,113 (165)

Trace-Norm Adversarial Examples

, 2020
White box adversarial perturbations are sought via iterative optimization algorithms most often minimizing an adversarial loss on a $l_p$ neighborhood of the original image, the so-called distortion set. Constraining the adversarial search with different norms results in disparately structured adversarial examples.
Kazemi, Ehsan, Kerdreux, Thomas, Wang, Liqiang   +2 more
openaire   +2 more sources

SAR-SPA: Incorporating Target Scattering Characteristic Parameters in Adversarial Example Generation for SAR Imagery

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Deep neural networks (DNNs)-based SAR target recognition models are susceptible to adversarial examples, which significantly reduce model robustness. Current methods for generating adversarial examples for SAR imagery primarily operate in the 2-D digital
Jiahao Cui, Jiale Duan, Binyan Luo, Hang Cao, Wang Guo, Haifeng Li   +5 more
doaj   +1 more source

Research on Image Adversarial Example Generation Method Based on SE-AdvGAN [PDF]

Jisuanji gongcheng
Adversarial examples are crucial for evaluating the robustness of Deep Neural Network (DNN) and revealing their potential security risks. The adversarial example generation method based on a Generative Adversarial Network (GAN), AdvGAN, has made ...
ZHAO Hong, SONG Furong, LI Wengai
doaj   +1 more source

Learning to Discriminate Adversarial Examples by Sensitivity Inconsistency in IoHT Systems. [PDF]

J Healthc Eng, 2023
Zhang H, Tan H, Zhu B, Wang L, Shafiq M, Gu Z.   +5 more
europepmc   +1 more source

Adversarial Examples for Electrocardiograms

, 2019
In recent years, the electrocardiogram (ECG) has seen a large diffusion in both medical and commercial applications, fueled by the rise of single-lead versions. Single-lead ECG can be embedded in medical devices and wearable products such as the injectable Medtronic Linq monitor, the iRhythm Ziopatch wearable monitor, and the Apple Watch Series 4 ...
Han, Xintian, Hu, Yuxuan, Foschini, Luca, Chinitz, Larry, Jankelson, Lior, Ranganath, Rajesh   +5 more
openaire   +2 more sources

Experimental demonstration of adversarial examples in learning topological phases. [PDF]

Nat Commun, 2022
Zhang H, Jiang S, Wang X, Zhang W, Huang X, Ouyang X, Yu Y, Liu Y, Deng DL, Duan LM.   +9 more
europepmc   +1 more source

DualFlow: Generating imperceptible adversarial examples by flow field and normalize flow-based model. [PDF]

Front Neurorobot, 2023
Liu R, Jin X, Hu D, Zhang J, Wang Y, Zhang J, Zhou W.   +6 more
europepmc   +1 more source

A Universal Detection Method for Adversarial Examples and Fake Images. [PDF]

Sensors (Basel), 2022
Lai J, Huo Y, Hou R, Wang X.
europepmc   +1 more source

Surreptitious Adversarial Examples through Functioning QR Code. [PDF]

J Imaging, 2022
Chindaudom A, Siritanawan P, Sumongkayothin K, Kotani K.   +3 more
europepmc   +1 more source

A decade of adversarial examples: a survey on the nature and understanding of neural network non-robustness

Компьютерная оптика
Adversarial examples, in the context of computer vision, are inputs deliberately crafted to deceive or mislead artificial neural networks. These examples exploit vulnerabilities in neural networks, resulting in minimal alterations to the original input ...
A.V. Trusov, E.E. Limonova, V.V. Arlazarov   +2 more
doaj   +1 more source