Results 71 to 80 of about 5,561,446 (302)
DLA: Dense-Layer-Analysis for Adversarial Example Detection [PDF]
European Symposium on Security and Privacy, 2019 In recent years Deep Neural Networks (DNNs) have achieved remarkable results and even showed superhuman capabilities in a broad range of domains. This led people to trust in DNN classifications even in security-sensitive environments like autonomous ...
Philip Sperl +3 more
semanticscholar +1 more source
IEEE Access, 2019 Deep neural networks (DNNs) have useful applications in machine learning tasks involving recognition and pattern analysis. Despite the favorable applications of DNNs, these systems can be exploited by adversarial examples.
Hyun Kwon +3 more
doaj +1 more source
Are Accuracy and Robustness Correlated?
, 2016 Machine learning models are vulnerable to adversarial examples formed by applying small carefully chosen perturbations to inputs that cause unexpected classification errors.
Boult, Terrance E. +2 more
core +1 more source
Adversarial Example Decomposition
, 2018 Research has shown that widely used deep neural networks are vulnerable to carefully crafted adversarial perturbations. Moreover, these adversarial perturbations often transfer across models. We hypothesize that adversarial weakness is composed of three sources of bias: architecture, dataset, and random initialization.
He, Horace +5 more
openaire +2 more sources
Meniscus Pixel Printing for Contact‐Lens Vision Sensing and Robotic Control
Advanced Functional Materials, EarlyView.A visual‐sensing contact lens is enabled by meniscus pixel printing (MPP), which rapidly patterns a 200 µm perovskite photodetector pixel in 1 s without masks, vacuum processing, or bulky equipment. A deep‐learning‐based super‐resolution reconstructs sparse on‐lens signals into 80 × 80 high‐resolution visual information, while AI‐driven eye‐tracking ...
Byung‐Hoon Gong +7 more
wiley +1 more source
Computational Modeling Meets 3D Bioprinting: Emerging Synergies in Cardiovascular Disease Modeling
Advanced Healthcare Materials, EarlyView.Emerging advances in three‐dimensional bioprinting and computational modeling are reshaping cardiovascular (CV) research by enabling more realistic, patient‐specific tissue platforms. This review surveys cutting‐edge approaches that merge biomimetic CV constructs with computational simulations to overcome the limitations of traditional models, improve ...
Tanmay Mukherjee +7 more
wiley +1 more source
DualFlow: Generating imperceptible adversarial examples by flow field and normalize flow-based model
Frontiers in Neurorobotics, 2023 Recent adversarial attack research reveals the vulnerability of learning-based deep learning models (DNN) against well-designed perturbations. However, most existing attack methods have inherent limitations in image quality as they rely on a relatively ...
Renyang Liu +10 more
doaj +1 more source
Human-Producible Adversarial Examples
, 2023 Submitted to ICLR ...
Khachaturov, David +5 more
openaire +2 more sources
Adversarial examples for models of code [PDF]
Proceedings of the ACM on Programming Languages, 2020 Neural models of code have shown impressive results when performing tasks such as predicting method names and identifying certain kinds of bugs. We show that these models are vulnerable to adversarial examples , and introduce a novel approach for attacking trained models of code using ...
Yefet, Noam, Alon, Uri, Yahav, Eran
openaire +2 more sources
Advanced Materials, EarlyView.This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley +1 more source