Results 31 to 40 of about 16,674 (259)
Adversarial examples in remote sensing [PDF]
Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2018 This paper considers attacks against machine learning algorithms used in remote sensing applications, a domain that presents a suite of challenges that are not fully addressed by current research focused on natural image data such as ImageNet. In particular, we present a new study of adversarial examples in the context of satellite image classification
Wojciech Czaja +4 more
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Adversarial Examples for Generative Models [PDF]
2018 IEEE Security and Privacy Workshops (SPW), 2018 We explore methods of producing adversarial examples on deep generative models such as the variational autoencoder (VAE) and the VAE-GAN. Deep learning architectures are known to be vulnerable to adversarial examples, but previous work has focused on the application of adversarial examples to classification tasks.
Jernej Kos, Ian Fischer, Dawn Song
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Adversarial Attack for SAR Target Recognition Based on UNet-Generative Adversarial Network
Remote Sensing, 2021 Some recent articles have revealed that synthetic aperture radar automatic target recognition (SAR-ATR) models based on deep learning are vulnerable to the attacks of adversarial examples and cause security problems.
Chuan Du, Lei Zhang
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Adversarial attacks and defenses in deep learning
网络与信息安全学报, 2020 The adversarial example is a modified image that is added imperceptible perturbations, which can make deep neural networks decide wrongly. The adversarial examples seriously threaten the availability of the system and bring great security risks to the ...
LIU Ximeng +2 more
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Adversarial Examples Generation Method Based on Random Translation Transformation [PDF]
Jisuanji gongcheng, 2022 The image classification model based on Deep Neural Network(DNN) can recognize images with a recognition degree that is even higher than that of human eyes.However, it is vulnerable to attacks from adversarial examples because of the fragility of the ...
LI Zheming, ZHANG Hengwei, MA Junqiang, WANG Jindong, YANG Bo
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A Multimodal Adversarial Attack Framework Based on Local and Random Search Algorithms
International Journal of Computational Intelligence Systems, 2021 Although many problems in computer vision and natural language processing have made breakthrough progress with neural networks, adversarial attack is a serious potential problem in many neural network- based applications.
Zibo Yi, Jie Yu, Yusong Tan, Qingbo Wu
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Are adversarial examples inevitable?
CoRR, 2018 ISBN:978-1-7138-7273 ...
Shafahi, Ali +4 more
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Boundary Adversarial Examples Against Adversarial Overfitting
CoRR, 2022 Standard adversarial training approaches suffer from robust overfitting where the robust accuracy decreases when models are adversarially trained for too long. The origin of this problem is still unclear and conflicting explanations have been reported, i.e., memorization effects induced by large loss data or because of small loss data and growing ...
Muhammad Zaid Hameed, Beat Buesser
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Adversarial Examples for Electrocardiograms
CoRR, 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 ...
Xintian Han +5 more
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IEEE Access, 2020 Person re-identification across a network of cameras, with disjoint views, has been studied extensively due to its importance in wide-area video surveillance.
Yu Zheng, Yantao Lu, Senem Velipasalar
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