Results 111 to 120 of about 447,373 (304)
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 +4 more
openaire +2 more sources
Federated learning with adversarial optimisation for secure and efficient 5G edge computing networks
With the evolution of 5G edge computing networks, privacy-aware applications are gaining significant attention due to their decentralised processing capabilities.
Jonathan White +5 more
core +1 more source
Precision Medical Sciences, EarlyView.Overview of multimodal artificial intelligence (AI) for precision therapeutics. Diverse biomedical data modalities, including multi‐omics, medical imaging, digital pathology, electronic health records, wearable‐device data, and molecular information, are integrated through multimodal AI frameworks incorporating fusion strategies, foundation models ...
Gedion Mengistu Dejen
wiley +1 more source
At present the perception system of autonomous vehicles is grounded on 3D vision technologies along with deep learning to process depth information. Although deep learning models for 3D perception give promising results, recent research demonstrates that
Perera, Asanka G. +3 more
core +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
Neural Network‐Based Runtime Monitoring and Control for Unknown Nonlinear Systems
International Journal of Robust and Nonlinear Control, EarlyView.ABSTRACT Real‐time system monitoring and stabilization become especially challenging when the system dynamics are unknown. This article introduces a novel design for monitoring and stabilizing unknown nonlinear systems with measurement noise. The design utilizes a generic modelling framework by decomposing the system into a known tunable linear ...
Jianglin Lan, Xianxian Zhao, Ron Patton
wiley +1 more source
Adversarial Attacks on Hyperbolic Networks
As hyperbolic deep learning grows in popularity, so does the need for adversarial robustness in the context of such a non-Euclidean geometry. To this end, this paper proposes hyperbolic alternatives to the commonly used FGM and PGD adversarial attacks.
Max van Spengler +2 more
openaire +4 more sources
The increased sophistication of smart grids has generated significant interest in employing unmanned aerial vehicles (UAVs) to monitor the operational condition of insulators, especially in identifying insulator defects to avoid substantial power loss ...
Islam, Rashidul +5 more
core +1 more source
How do humans perceive adversarial text? A reality check on the validity and naturalness of word-based adversarial attacks [PDF]
, 2023 peer reviewedNatural Language Processing (NLP) models based on Machine Learning (ML) are susceptible to adversarial attacks -- malicious algorithms that imperceptibly modify input text to force models into making incorrect predictions.
GHAMIZI, Salah +2 more
core +1 more source
Sustainable Development, EarlyView.ABSTRACT In today's volatile, uncertain, complex, and ambiguous (VUCA) business environment, organizations face mounting pressure to develop agile and resilient supply chains capable of withstanding increasingly frequent disruptions. At the same time, sustainability has evolved into a strategic necessity, requiring firms to balance competitiveness with
Arsalan Zahid Piprani +4 more
wiley +1 more source