Results 51 to 60 of about 17,381 (301)

Sex‐Stratified Association of Regional Dopamine Transporter Binding With Disease Progression in Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To clarify the clinical relevance of dopamine transporter single‐photon emission computed tomography (DAT‐SPECT) abnormalities in amyotrophic lateral sclerosis (ALS), with a prespecified focus on sex‐stratified associations with disease progression and short‐term prognosis.
Tomoya Kawazoe, Keizo Sugaya, Kentaro Hayashi, Keiko Hino, Yasuhiro Nakata, Kota Bokuda, Toshio Shimizu, Kazushi Takahashi   +7 more
wiley   +1 more source

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

Arthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +1 more source

Matrix Expression of Convolution and Its Generalized Continuous Form

, 2020
In this paper, we consider the matrix expression of convolution, and its generalized continuous form. The matrix expression of convolution is effectively applied in convolutional neural networks, and in this study, we correlate the concept of convolution
Young Hee Geum, Hwajoon Kim, Arjun Kumar Rathie   +2 more
core   +1 more source

General Logarithmic Image Processing Convolution [PDF]

IEEE Transactions on Image Processing, 2006
The logarithmic image processing model (LIP) is a robust mathematical framework, which, among other benefits, behaves invariantly to illumination changes. This paper presents, for the first time, two general formulations of the 2-D convolution of separable kernels under the LIP paradigm.
José M. Palomares, Jesús González 0001, Eduardo Ros Vidal, Alberto Prieto   +3 more
openaire   +2 more sources

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

GENERALIZED DUNKL CONVOLUTION OPERATOR [PDF]

, 2017
В работе рассматривается обобщенный оператор Данкла и его свойства. Изучается построенный по нему оператор свертки.The paper considers the generalized Dunkl operator and its properties.
Рахимова Алсу Ильдаровна, Напалков В.В.   +1 more
core  

New convolutions for the Hartley integral transform imbedded in the Banach algebras and convolution-type integral equations

Demonstratio Mathematica
This article presents two types of the new convolutions for the Hartley integral transform associated with the Hermite functions, gives rise to the identification of some commutative and non-commutative Banach algebras, and to the Young inequalities ...
Tuan Nguyen Minh, Giang Bui Thi, Ha Quan Thai   +2 more
doaj   +1 more source

Conditional Fourier-Feynman Transforms with Drift on a Function Space

Journal of Function Spaces, 2019
In this paper we derive change of scale formulas for conditional analytic Fourier-Feynman transforms and conditional convolution products of the functions which are the products of generalized cylinder functions and the functions in a Banach algebra ...
Dong Hyun Cho, Suk Bong Park
doaj   +1 more source

Convolutional Generation of Textured 3D Meshes

CoRR, 2020
NeurIPS 2020, Oral presentation.
Pavllo, Dario, Spinks, Graham, Hofmann, Thomas, Moens, Marie-Francine, Lucchi, Aurelien   +4 more
openaire   +5 more sources

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source