Bioethics, EarlyView.ABSTRACT Many controversies in medical ethics, particularly those involving conflicts between parents and medical staff over decisions about child patients, are challenging to manage without causing significant polarization and communication issues. This is primarily because the parties involved—parents and physicians—operate at different epistemic ...
Chiara Innorta
wiley +1 more source
Untargeted white-box adversarial attack to break into deep leaning based COVID-19 monitoring face mask detection system. [PDF]
Multimed Tools Appl, 2023 Sheikh BUH, Zafar A.
europepmc +1 more source
ASTrA: Adversarial Self-supervised Training with Adaptive-Attacks
Existing self-supervised adversarial training (self-AT) methods rely on hand-crafted adversarial attack strategies for PGD attacks, which fail to adapt to the evolving learning dynamics of the model and do not account for instance-specific ...
Saini, Rajkumar +5 more
core
An improved genetic algorithm and its application in neural network adversarial attack. [PDF]
PLoS One, 2022 Yang D, Yu Z, Yuan H, Cui Y.
europepmc +1 more source
Boosting Adversarial Transferability Through Adversarial Attack Enhancer
Adversarial attacks against deep learning models achieve high performance in white-box settings but often exhibit low transferability in black-box scenarios, especially against defended models.
Hong Huang, Wenli Zeng, Jixin Chen
core +1 more source
Visualizing Image Segmentation Network Behavior Through the Lens of Scale Space Analysis
Computer Graphics Forum, EarlyView.Abstract Deep neural networks are widely used for image segmentation, also in sensitive applications such as medical imaging or autonomous driving. However, few explainable AI methods are available that help developers understand such networks beyond classification.
A. C. Mikliss, T. Schultz
wiley +1 more source
How Resilient Are Deep Learning Models in Medical Image Analysis? The Case of the Moment-Based Adversarial Attack (Mb-AdA). [PDF]
Biomedicines, 2022 Maliamanis TV +2 more
europepmc +1 more source
SPINE: VAE‐driven Counterfactuals for Decision Boundary Maps
Computer Graphics Forum, EarlyView.Abstract As Deep Learning models become increasingly complex, Explainable AI becomes essential for deploying machine learning classifiers. Decision Boundary Mapping (DBM) is a technique for visualizing a classifier's global decision boundary. Despite their relative success, current DBM methods rely on global inverse multidimensional projections that ...
I.M. Bloemen, V. Prasad, F. V. Paulovich
wiley +1 more source
RetouchUAA: Unconstrained Adversarial Attack via Image Retouching
, 2023 Deep Neural Networks (DNNs) are susceptible to adversarial examples. Conventional attacks generate controlled noise-like perturbations that fail to reflect real-world scenarios and hard to interpretable.
Xie, Mengda, He, Yiling, Fang, Meie
core +1 more source
Textile and colour defect detection using deep learning methods
Coloration Technology, EarlyView.Abstract Recent advances in deep learning (DL) have significantly enhanced the detection of textile and colour defects. This review focuses specifically on the application of DL‐based methods for defect detection in textile and coloration processes, with an emphasis on object detection and related computer vision (CV) tasks.
Hao Cui +2 more
wiley +1 more source