Results 191 to 200 of about 2,268,403 (339)
A CRDNet‐Based Watermarking Algorithm for Fused Visible–Infrared Images
CRDnet includes encoders and decoders based on residual and dense structures, a fusion network robust to 12 visible and infrared image fusion algorithms, and predictors for predicting watermarked infrared images. The encoder and decoder incorporate preprocessing steps, attention mechanisms, and activation functions suitable for infrared images.
Yu Bai +4 more
wiley +1 more source
MedRDF: A Robust and Retrain-Less Diagnostic Framework for Medical Pretrained Models Against Adversarial Attack [PDF]
Mengting Xu, Tao Zhang, Daoqiang Zhang
openalex +1 more source
Cardiovascular diseases are leading death causes; electrocardiogram (ECG) analysis is slow, motivating machine learning and deep learning. This study compares deep convolutional generative adversarial network, conditional GAN, and Wasserstein GAN with gradient penalty (WGAN‐GP) for synthetic ECG spectrograms; Fréchet Inception Distance (FID) and ...
Giovanny Barbosa‐Casanova +3 more
wiley +1 more source
Explainability-driven adversarial robustness assessment for generalized deepfake detectors
The capabilities of generative models to produce high-quality fake images require deepfake detectors to be accurate and have strong generalization performance.
Lorenzo Cirillo +2 more
doaj +1 more source
On Adversarial Robustness of Language Models in Transfer Learning [PDF]
Bohdan Turbal +3 more
openalex +1 more source
Robust Dysarthric Speech Recognition with GAN Enhancement and LLM Correction
This study tackles dysarthric speech recognition by combining generative adversarial network (GAN)‐generated synthetic data with large language model (LLM)‐based error correction. The approach integrates three key elements: an improved CycleGAN to generate synthetic dysarthric speech for data augmentation, a multimodal automatic speech recognition core
Yibo He +3 more
wiley +1 more source
Improving Adversarial Robustness via Phase and Amplitude-aware Prompting [PDF]
Yibo Xu +3 more
openalex +1 more source
Feature Disentangling and Combination Implemented by Spin–Orbit Torque Magnetic Tunnel Junctions
Spin–orbit torque magnetic tunnel junctions (SOT‐MTJs) enable efficient feature disentangling and integration in image data. A proposed algorithm leverages SOT‐MTJs as true random number generators to disentangle and recombine features in real time, with experimental validation on emoji and facial datasets.
Xiaohan Li +15 more
wiley +1 more source
Correction: Exploring biologically inspired mechanisms of adversarial robustness [PDF]
Konstantin Holzhausen +4 more
openalex +1 more source
Feature from recent image foundation models (DINOv2) are useful for vision tasks (segmentation, object localization) with little or no human input. Once upsampled, they can be used for weakly supervised micrograph segmentation, achieving strong results when compared to classical features (blurs, edge detection) across a range of material systems.
Ronan Docherty +2 more
wiley +1 more source

