Results 111 to 120 of about 3,042,897 (294)
An Integrated Artificial Intelligence Framework for Nanomedicine Engineering
Advanced Science, EarlyView.This review outlines a closed‐loop AI ecosystem for nanomedicine engineering. By synergizing multimodal data harmonization, objective‐driven AI architectures, and automated high‐throughput validation, this “Design‐Make‐Test‐Analyze” (DMTA) workflow transforms traditional heuristic formulation into a predictive, self‐optimizing paradigm, accelerating ...
Meichen Dong +10 more
wiley +1 more source
Physics‐Guided Multi‐Channel Restoration for Efficient and Accurate Atomic Force Microscopy Imaging
Advanced Science, EarlyView.Schematic figure of restoring noisy atomic force micrscopy (AFM) image via physics‐guided multi‐channel restoration. The lighter neural network models with multiple‐channel input from auxiliary signals outperforms heavier model with single‐channel input.
Jaeuk Sung +13 more
wiley +1 more source
Annealed Generative Adversarial Networks
CoRR, 2017 9 pages, 6 ...
Arash Mehrjou +2 more
openaire +2 more sources
Physical Unclonable Functions From Microwave Metasurface Fingerprints
Advanced Electronic Materials, EarlyView.Nominally identical metasurfaces fabricated through standard PCB processes inevitably contain microscopic fabrication imperfections. This work demonstrates that these unavoidable electromagnetic deviations can serve as unique physical unclonable fingerprints for wireless authentication.
Guanxiong Shen +4 more
wiley +1 more source
Advanced Energy Materials, EarlyView.The application of a generative diffusion model, enhanced with a training data augmentation pipeline retaining the manufacturing process context of electrode microstructures, leads to improved fidelity of the through‐plane tortuosity factor in the AI generated samples.
Victor Ramirez‐Camacho +5 more
wiley +1 more source
Rapid measurements and phase transition detections made simple by AC-GANs
SciPost Physics CoreIn recent years, significant attention has been paid to using end-to-end neural networks for analyzing Monte Carlo data. However, the exploration of non-end-to-end generative adversarial neural networks remains limited.
Jiewei Ding, Ho-Kin Tang, Wing Chi Yu
doaj +1 more source
Tympanic Membrane Generation with Generative Adversarial Networks
, 2021 © 2021 IEEE.Obtaining sufficient original data in most studies in the field of medical pattern recognition is a difficult and time consuming process. Different data augmentation methods are used to increase the amount of data to be used to train these ...
M. Elif Karsligil +5 more
core +1 more source
Unrolled Generative Adversarial Networks
CoRR, 2016 We introduce a method to stabilize Generative Adversarial Networks (GANs) by defining the generator objective with respect to an unrolled optimization of the discriminator. This allows training to be adjusted between using the optimal discriminator in the generator's objective, which is ideal but infeasible in practice, and using the current value of ...
Luke Metz +3 more
openaire +3 more sources
Advanced Intelligent Discovery, EarlyView.Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto +3 more
wiley +1 more source