Results 231 to 240 of about 597,354 (286)

Challenges and Opportunities in Machine Learning for Light‐Emitting Polymers

Macromolecular Rapid Communications, EarlyView.
The performance of light‐emitting polymers emerges from coupled effects of chemical diversity, morphology, and exciton dynamics across multiple length scales. This Perspective reviews recent design strategies and experimental challenges, and discusses how machine learning can unify descriptors, data, and modeling approaches to efficiently navigate ...
Tian Tian, Yinyin Bao
wiley   +1 more source

Cenozoic evolution of earth's strongest geoid low illuminates mantle dynamics beneath Antarctica. [PDF]

Sci Rep
Glišović P, Forte AM.
europepmc   +1 more source

Mass spectrometry imaging of N‐linked glycans: Fundamentals and recent advances

Mass Spectrometry Reviews, EarlyView.
Abstract With implications in several medical conditions, N‐linked glycosylation is one of the most important posttranslation modifications present in all living organisms. Due to their nontemplate synthesis, glycan structures are extraordinarily complex and require multiple analytical techniques for complete structural elucidation.
Tana V. Palomino, David C. Muddiman
wiley   +1 more source

Deep learning driven prediction and comparative study of surrounding rock deformation in high speed railway tunnels. [PDF]

Sci Rep
Yang Z, Cheng Z, Wu D.
europepmc   +1 more source

Jointly Learned 3D Non‐Cartesian Sampling With Wave Encoding and Reconstruction for Neurovascular Phase Contrast MRI

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To develop accelerated 3D phase contrast (PC) MRI using jointly learned wave encoding and reconstruction. Methods Pseudo‐fully sampled neurovascular 4D flow data (N = 40) and a simulation framework were used to learn phase encoding locations, wave readout parameters, and model‐based reconstruction network (MoDL) for a rapid 3D PC scan (
Chenwei Tang, Brock W. Jolicoeur, James Rice, Caroline A. Doctor, Zaynab S. Yardim, Leonardo A. Rivera‐Rivera, Laura B. Eisenmenger, Kevin M. Johnson   +7 more
wiley   +1 more source

Denoising: a powerful building block for imaging, inverse problems and machine learning. [PDF]

Philos Trans A Math Phys Eng Sci
Milanfar P, Delbracio M.
europepmc   +1 more source

Accelerating Multiparametric Quantitative MRI Using Self‐Supervised Scan‐Specific Implicit Neural Representation With Model Reinforcement

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To develop a self‐supervised scan‐specific deep learning framework for reconstructing accelerated multiparametric quantitative MRI (qMRI). Methods We propose REFINE‐MORE (REference‐Free Implicit NEural representation with MOdel REinforcement), combining an implicit neural representation (INR) architecture with a model reinforcement ...
Ruimin Feng, Albert Jang, Xingxin He, Fang Liu   +3 more
wiley   +1 more source

LGFUNet: A Water Extraction Network in SAR Images Based on Multiscale Local Features with Global Information. [PDF]

Sensors (Basel)
Bai X, Zhang Y, Wei J.
europepmc   +1 more source

Informed Dictionary‐Guided Monte Carlo Inversion for Robust and Reproducible Multidimensional MRI

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To develop a robust and efficient multidimensional MRI (MD‐MRI) data processing framework for accurately estimating joint frequency‐dependent diffusion‐relaxation distributions, while overcoming computational limitations and noise instability inherent to Monte Carlo (MC) inversion.
Joon Sik Park, Eppu Manninen, Yihong Yang, Dan Benjamini   +3 more
wiley   +1 more source