Results 101 to 110 of about 447,373 (304)

Harmonic Adversarial Attack Method

CoRR, 2018
Adversarial attacks find perturbations that can fool models into misclassifying images. Previous works had successes in generating noisy/edge-rich adversarial perturbations, at the cost of degradation of image quality. Such perturbations, even when they are small in scale, are usually easily spottable by human vision.
Wen Heng, Shuchang Zhou 0001, Tingting Jiang 0001   +2 more
openaire   +2 more sources

Promises and limitations of deep learning for predicting knee osteoarthritis progression from medical imaging: A systematic review

Knee Surgery, Sports Traumatology, Arthroscopy, EarlyView.
Abstract Purpose To systematically evaluate the performance, methodological quality, and translational barriers of deep learning (DL) models for predicting knee osteoarthritis (KOA) progression from medical imaging. Methods Following PRISMA guidelines, we searched PubMed, Scopus, and Web of Science (inception to June 2026) for peer‐reviewed studies ...
Amna Gillani, Rüdiger von Eisenhart‐Rothe, Klaus Woertler, Michael T. Hirschmann, Daniel Rueckert, Florian Hinterwimmer   +5 more
wiley   +1 more source

A Comprehensive Risk Analysis Method for Adversarial Attacks on Biometric Authentication Systems

IEEE Access
Recent threats to deep learning-based biometric authentication systems stem from adversarial attacks exploiting vulnerabilities in deep learning models. While existing studies extensively analyze the risk of such attacks, they primarily focus on isolated
Seong Hee Park, Soo-Hyun Lee, Min Young Lim, Pyo Min Hong, Youn Kyu Lee   +4 more
doaj   +1 more source

Adversarial Vulnerability and Defense in Human Detection: An Experimental Study Using FGSM, PGD, and Adversarial Training on the HERIDAL Dataset [PDF]

International Journal of Innovative Solutions in Engineering
Adversarial attacks pose a serious threat to the reliability of modern artificial intelligence systems, especially in computer vision. Although such attacks rely on very small, often imperceptible perturbations of the input data, they can cause a ...
Marijana Bandić, Maja Kovačić, Fran Pavlović   +2 more
doaj   +1 more source

Exploiting Machine Learning to Subvert Your Spam Filter [PDF]

, 2008
Using statistical machine learning for making security decisions introduces new vulnerabilities in large scale systems. This paper shows how an adversary can exploit statistical machine learning, as used in the SpamBayes spam filter, to render it useless—
Nelson, Blaine, Tygar, J. D., Xia, Kai, Rubinstein, Benjamin I. P., Sutton, Charles, Barreno, Marco, Chi, Fuching Jack, Joseph, Anthony D., Saini, Udam   +8 more
core  

Harnessing Aggregation‐Induced Emission for Advanced Disease Diagnosis: Mechanisms, Strategies and Future Perspectives

Medicine Bulletin, EarlyView.
The figure was created in BioRender.com. ABSTRACT Accurate and early diagnosis remains a key challenge in modern disease management. Conventional diagnostic methods often suffer from limitations in sensitivity, spatial resolution, and practical usability.
Zizhuo Du, Li Song, Xingrui Chen, Jun Jing, Yingchen Wang, Yue Jiang, Jiahui Gao, Dan Li, Feiran Xie, Peihong Xiao, Ben Zhong Tang   +10 more
wiley   +1 more source

Dynamic Performance Enhancement of a High‐Agility Hypersonic Mechanical System via a Learning‐Augmented Robust Control Architecture

International Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT The design of control systems for high‐agility mechanical systems operating in extreme environments is a significant challenge in nonlinear dynamics. This paper addresses the complex dynamic control problem of a hypersonic interceptor, modeled as a multi‐input multi‐output (MIMO) mechanical system characterized by strong aerodynamic cross ...
Mohammad Mahdi Soori, Seyed Hossein Sadati   +1 more
wiley   +1 more source

Adversarial Attacks and Defences: A Survey

CoRR, 2018
Deep learning has emerged as a strong and efficient framework that can be applied to a broad spectrum of complex learning problems which were difficult to solve using the traditional machine learning techniques in the past. In the last few years, deep learning has advanced radically in such a way that it can surpass human-level performance on a number ...
Anirban Chakraborty 0003, Manaar Alam, Vishal Dey, Anupam Chattopadhyay, Debdeep Mukhopadhyay   +4 more
openaire   +2 more sources

Interdiction Models and Heuristics for Graph Propagation

Networks, EarlyView.
ABSTRACT Given a graph G=(V,E)$$ G=\left(V,E\right) $$ and a set S⊂V$$ S\subset V $$ of activated/infected nodes, we consider the problem of determining the set of c$$ c $$ nodes that minimizes the network propagation on the subgraph that results from the removal of those c$$ c $$ nodes. To measure network propagation, we assume that a node i$$ i $$ is
Agostinho Agra, José Maria Samuco
wiley   +1 more source

Using art history to explore society's changing connections with agriculture

PLANTS, PEOPLE, PLANET, EarlyView.
Food insecurity is a looming challenge that especially affects those least fortunate. Consumer food choices have a substantial impact on the sustainability of current food systems. Here, we use art as a lens through which to consider our contemporary and historical relationship to one of the world's most crucial crops, the potato, in the context of the
Edward F. Hill‐King, Martin R. McAinsh, Michael R. Roberts   +2 more
wiley   +1 more source