Results 81 to 90 of about 62,392 (177)

Opt: A Domain Specific Language for Non-linear Least Squares Optimization in Graphics and Imaging

, 2016
Many graphics and vision problems can be expressed as non-linear least squares optimizations of objective functions over visual data, such as images and meshes.
Bernstein, Gilbert, DeVito, Zachary, Fisher, Matthew, Hanrahan, Pat, Mara, Michael, Nießner, Matthias, Ragan-Kelley, Jonathan, Theobalt, Christian, Zollhöfer, Michael   +8 more
core   +1 more source

Machine Learning for Predictive Modeling in Nanomedicine‐Based Cancer Drug Delivery

Med Research, EarlyView.
The integration of AI/ML into nanomedicine offers a transformative approach to therapeutic design and optimization. Unlike conventional empirical methods, AI/ML models (such as classification, regression, and neural networks) enable the analysis of complex clinical and formulation datasets to predict optimal nanoparticle characteristics and therapeutic
Rohan Chand Sahu, Sanchit Arora, Dinesh Kumar, Ashish Kumar Agrawal   +3 more
wiley   +1 more source

Fast and numerically stable circle fit

, 2015
We develop a new algorithm for fitting circles that does not have drawbacks commonly found in existing circle fits. Our fit achieves ultimate accuracy (to machine precision), avoids divergence, and is numerically stable even when fitting circles get ...
Abdul-Rahman, Houssam, Chernov, Nikolai
core   +1 more source

Prediction of the Mechanical Properties of the Additive Friction Stir‐Deposited Al2219 Using Machine Learning

Materials Genome Engineering Advances, EarlyView.
In this work, three prediction machine learning (ML) models (MLP, RBF, BP) are developed to predict the ultimate tensile strength (UTS) and elongation (EL) of the AFSDed Al2219 samples. ABSTRACT Additive friction stir deposition (AFSD) is an effective method for fabricating high‐performance deposits, with process parameters directly influencing the ...
Chan Wa Tam, Qian Qiao, Xiaowei Chen, Wai I Lam, Xiumei Gong, Yongyong Lin, Hongchang Qian, Dawei Guo, Dawei Zhang, Chi Tat Kwok, Lap Mou Tam   +10 more
wiley   +1 more source

Analytical and Numerical Soliton Solutions of the Shynaray II‐A Equation Using the G′G,1G$$ \left(\frac{G^{\prime }}{G},\frac{1}{G}\right) $$‐Expansion Method and Regularization‐Based Neural Networks

Mathematical Methods in the Applied Sciences, EarlyView.
ABSTRACT Nonlinear differential equations play a fundamental role in modeling complex physical phenomena across solid‐state physics, hydrodynamics, plasma physics, nonlinear optics, and biological systems. This study focuses on the Shynaray II‐A equation, a relatively less‐explored parametric nonlinear partial differential equation that describes ...
Aamir Farooq, H. W. A. Riaz, Sadique Rehman, M. Mamun Miah, Wen Xiu Ma   +4 more
wiley   +1 more source

Uma implementação do algoritmo Levenberg-Marquardt dividido para aplicações em visão computacional.

Semina: Ciências Exatas e Tecnológicas, 2009
Em diversas aplicações da visão computacional, é necessário estimar-se, em um modelo, os parâmetros que melhor se ajustam a um conjunto de dados experimentais. Nesses casos, um algoritmo de minimização pode ser utilizado.
José Alexandre de França, Maria Bernadete de Morais França, Marcela Hitomi Koyama, Tiago Polizer da Silva   +3 more
doaj   +1 more source

Relaxivity of Gadobutrol and Gadoteric Acid in Cerebrospinal Fluid at 3T

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose The aim was to estimate T1 relaxivity of gadobutrol and gadoteric acid in cerebrospinal fluid (CSF) at 3T, to support research on CSF‐flow and the glymphatic system in humans utilizing T1 mapping after intrathecal injection. Methods Using a phantom, relaxivity was estimated for gadobutrol and gadoteric acid in lumbar CSF and an ...
Sofia Behndig, Anders Garpebring, Daniel Dahlgren Lindström, Jan Malm, Anders Wåhlin, Anders Eklund   +5 more
wiley   +1 more source

Ellipsoid‐Based Interval‐Type Uncertainty Model Updating Based on Riemannian Manifold and Gaussian Process Model

International Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT Modern engineering systems require advanced uncertainty‐aware model updating methods that address parameter correlations beyond conventional interval analysis. This paper proposes a novel framework integrating Riemannian manifold theory with Gaussian Process Regression (GPR) for systems governed by Symmetric Positive‐Definite (SPD) matrix ...
Yanhe Tao, Qintao Guo, Jin Zhou, Cheng Yi   +3 more
wiley   +1 more source

Design of artificial neural networks for darcy-forchheimer flow of boger hybrid nanofluid with CattaneoChristov theory: Thermofluidic applications

International Journal of Thermofluids
This study investigates the effects of Marangoni convection on the Darcy-Forchheimer flow of MHD Boger fluid across a sheet using CattaneoChristov heat and mass flux model using artificial neural networks and the Levenberg–Marquardt scheme.
Hussein Ibrahim Hussein, Abdulbasit A. Darem, Asma A. Alhashmi, Nodira Nazarova, Jihad Younis, Munawar Abbas, Hakim AL Garalleh, Amr Alalawi   +7 more
doaj   +1 more source

Solid Particle Erosion and Predictive Modeling of Epoxy Composites Reinforced With Diatom Frustules

Polymer Composites, EarlyView.
Schematic representation of the solid particle erosion process and predictive modeling workflow for diatom frustule‐reinforced epoxy composites, illustrating the test setup, erosion response curve, and filler‐matrix interaction. ABSTRACT This study examines the solid particle erosion wear behavior of epoxy composites reinforced with 5–20 wt% calcined ...
Elif Gültürk, Eser Yarar, Orkan Baran Korkusuz, Aleyna Kara, Tamer Sınmazçelik   +4 more
wiley   +1 more source