Invisible CMOS Camera Dazzling for Conducting Adversarial Attacks on Deep Neural Networks. [PDF]
Sensors (Basel)Stein Z, Hazan A, Stern A.
europepmc +1 more source
Building centaur responders: is emergency management ready for artificial intelligence?
Disasters, Volume 50, Issue 3, July 2026.Abstract This article examines the preparedness of emergency management (EM) for addressing questions pertaining to artificial intelligence (AI), encompassing its benefits to EM missions, the potential biases, the societal impacts, and more. We pinpoint two key shortcomings in early EM research on AI: (i) insufficient discussion of both AI's history ...
Christopher Whyte +1 more
wiley +1 more source
adverSCarial: assessing the vulnerability of single-cell RNA-sequencing classifiers to adversarial attacks. [PDF]
BioinformaticsFievet G +3 more
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Regularization Meets Enhanced Multi-Stage Fusion Features: Making CNN More Robust against White-Box Adversarial Attacks. [PDF]
Sensors (Basel), 2022 Zhang J, Maeda K, Ogawa T, Haseyama M.
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AI Magazine, Volume 47, Issue 2, Summer 2026.Abstract AI systems are rapidly transitioning from laboratory demonstrations to decision‐making technologies deployed in high‐stakes domains. Yet reliability remains a primary obstacle to responsible adoption: discriminative models can be confidently wrong under out‐of‐distribution (OOD) inputs, and foundation models (FMs) such as large language models
Sean Du
wiley +1 more source
Tailoring adversarial attacks on deep neural networks for targeted class manipulation using DeepFool algorithm. [PDF]
Sci RepLabib SMFR +4 more
europepmc +1 more source
Universal adversarial attacks on deep neural networks for medical image classification. [PDF]
BMC Med Imaging, 2021 Hirano H, Minagi A, Takemoto K.
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A Survey for Deep Reinforcement Learning Based Network Intrusion Detection
Applied AI Letters, Volume 7, Issue 2, June 2026.This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang +3 more
wiley +1 more source
Highly Accurate Adaptive Federated Forests Based on Resistance to Adversarial Attacks in Wireless Traffic Prediction. [PDF]
Sensors (Basel)Wang L +7 more
europepmc +1 more source
Natural Images Allow Universal Adversarial Attacks on Medical Image Classification Using Deep Neural Networks with Transfer Learning. [PDF]
J Imaging, 2022 Minagi A, Hirano H, Takemoto K.
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