Results 71 to 80 of about 107,198 (316)
An Extended Study of Human-like Behavior under Adversarial Training
, 2023 Neural networks have a number of shortcomings. Amongst the severest ones is the sensitivity to distribution shifts which allows models to be easily fooled into wrong predictions by small perturbations to inputs that are often imperceivable to humans and ...
Gavrikov, Paul +2 more
core +1 more source
Advanced Robotics Research, EarlyView.This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi +2 more
wiley +1 more source
DEEP DETECTOR HEALTH MANAGEMENT UNDER ADVERSARIAL CAMPAIGNS
International Journal of Prognostics and Health Management, 2019 Machine learning models are vulnerable to adversarial inputs that induce seemingly unjustifiable errors. As automated classifiers are increasingly used in industrial control systems and machinery, these adversarial errors could grow to be a serious ...
Javier Echauz +6 more
doaj +1 more source
A Robust Adversarial Example Attack Based on Video Augmentation
Applied Sciences, 2023 Despite the success of learning-based systems, recent studies have highlighted video adversarial examples as a ubiquitous threat to state-of-the-art video classification systems.
Mingyong Yin +3 more
doaj +1 more source
, 2000 While there is a great deal of sophistication in modern cryptology, simple (and simplistic) explanations of cryptography remain useful and perhaps necessary. Many of the explanations are informal; others are embodied in formal methods, particularly in formal methods for the analysis of security protocols.
openaire +1 more source
Defending Against Adversarial Attacks with Camera Image Pipelines
, 2023 Existing neural networks for computer vision tasks are vulnerable to adversarial attacks: adding imperceptible perturbations to the input images can fool these models into making a false prediction on an image that was correctly predicted without the ...
Zhang, Yuxuan
core
Advanced Robotics Research, EarlyView.This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source
Exploring Adversarial Attacks and Defences for Fake Twitter Account Detection
, 2020 Social media has become very popular and important in people’s lives, as personal ideas, beliefs and opinions are expressed and shared through them. Unfortunately, social networks, and specifically Twitter, suffer from massive existence and perpetual ...
Nikolaos Pitropakis +7 more
core +1 more source
Higher-Resolution-and-Less-Noisy-Seismic-Images-An-Application-of-Generative-Adversarial-Neural-Net
, 2022 An application of generative adversarial networks to seismic data processing (resolution ehancement and denoising). This is a repository for the paper "Higher Resolution and Less Noisy Seismic Images: An Application of Generative Adversarial Neural Net" (
Lei Lin (12656614)
core +1 more source
Solid Harmonic Wavelet Bispectrum for Image Analysis
Advanced Science, EarlyView.The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown +3 more
wiley +1 more source