Results 81 to 90 of about 6,497 (247)

Review of Research on Adversarial Attack in Three Kinds of Images [PDF]

Jisuanji kexue yu tansuo
In recent years, there have been numerous breakthroughs in deep learning, leading to the expansion of applications based on deep learning into a wide range of fields.
XU Yuhui, PAN Zhisong, XU Kun
doaj   +1 more source

Preparing for Tomorrow's Teamwork: Insights From eSports on How Human Expertise Shapes Training Needs for AI‐Integrated Work

Journal of Organizational Behavior, EarlyView.
ABSTRACT As organizations increasingly adopt human‐AI teams (HATs), understanding how to enhance team performance is paramount. A crucially underexplored area for supporting HATs is training, particularly helping human teammates to work with these inorganic counterparts.
Caitlin M. Lancaster, Christopher Flathmann, Jennifer Hsu, Nathan J. McNeese, Thomas A. O'Neill, Eduardo Salas   +5 more
wiley   +1 more source

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

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

Link Prediction Adversarial Attack

CoRR, 2018
Deep neural network has shown remarkable performance in solving computer vision and some graph evolved tasks, such as node classification and link prediction. However, the vulnerability of deep model has also been revealed by carefully designed adversarial examples generated by various adversarial attack methods.
Jinyin Chen, Ziqiang Shi, Yangyang Wu, Xuanheng Xu, Haibin Zheng   +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

Ctta: a novel chain-of-thought transfer adversarial attacks framework for large language models

Cybersecurity
Recent studies have indicated that large language models (LLMs) remain susceptible to adversarial attacks, despite enhanced robustness through the chain-of-thought (CoT) capability.
Xinxin Yue, Zhiyong Zhang, Junchang Jing, Weiguo Wang   +3 more
doaj   +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

Llm-ga: A gradient-based multi-label adversarial attack by large language models

Complex & Intelligent Systems
Deep neural networks (DNNs) are highly sensitive to small, meticulously crafted perturbations, which have been utilized in adversarial attacks, threatening the reliability of DNNs in practical applications. Current adversarial attack methods rely heavily
Yujiang Liu, Yamin Hu, Zhijian Chen, Shiyin Wang, Wenjian Luo   +4 more
doaj   +1 more source