Results 51 to 60 of about 54,415 (225)
A feasible and automatic free tool for T1 and ECV mapping [PDF]
, 2017 Purpose: Cardiac magnetic resonance (CMR) is a useful non-invasive tool for characterizing tissues and detecting myocardial fibrosis and edema. Estimation of extracellular volume fraction (ECV) using T1 sequences is emerging as an accurate biomarker in ...
Altabella, Luisa +8 more
core +1 more source
Predicting Performance of Hall Effect Ion Source Using Machine Learning
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +1 more source
Five planets and an independent confirmation of HD 196885Ab from Lick Observatory [PDF]
, 2009 We present time series Doppler data from Lick Observatory that reveal the presence of long-period planetary companions orbiting nearby stars. The typical eccentricity of these massive planets are greater than the mean eccentricity of known exoplanets ...
Andrew Howard +33 more
core +2 more sources
Machine Learning‐Driven Variability Analysis of Process Parameters for Semiconductor Manufacturing
Advanced Intelligent Systems, EarlyView.This research presents a machine learning approach that integrates nonlinear variation decomposition (NLVD) with statistical techniques to quantify the contribution of individual unit processes to performance and variance of figure of merit (FoM) at the LOT level.
Sinyeong Kang +6 more
wiley +1 more source
Online Signature for Attendance Verification System using Levenberg-Marquardt Neural Network [PDF]
, 2015 This work focuses on the application of Levenberg-Marquardt based Back-propagation Neural Network for training features extracted from online signature images.
Adefuminiyi, Morakinyo A. +2 more
core +1 more source
Confidence-aware Levenberg-Marquardt optimization for joint motion estimation and super-resolution
, 2016 Motion estimation across low-resolution frames and the reconstruction of high-resolution images are two coupled subproblems of multi-frame super-resolution.
Bercea, Cosmin +2 more
core +1 more source
Local Levenberg-Marquardt Algorithm for Learning Feedforwad Neural Networks [PDF]
Journal of Artificial Intelligence and Soft Computing Research, 2020 Abstract This paper presents a local modification of the Levenberg-Marquardt algorithm (LM). First, the mathematical basics of the classic LM method are shown. The classic LM algorithm is very efficient for learning small neural networks. For bigger neural networks, whose computational complexity grows significantly, it makes this method
Jaroslaw Bilski +3 more
openaire +1 more source
Advanced Intelligent Systems, EarlyView.This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi +3 more
wiley +1 more source
Modeling Leachate Generation Using Artificial Neural Networks [PDF]
آب و فاضلاب, 2011 In this study, a neural network model is proposed for modeling leachate flow-rate in a municipal solid waste landfill site. After training, the neural network model predicts leachate generation based on meteorological data and leachate characteristics ...
Mohammad Javad Zoqi, Mohsen Saeedi
doaj
Enhancement of Healthcare Data Transmission using the Levenberg-Marquardt Algorithm
CoRR, 2022 14 pages.
Angela An, James Jin Kang
openaire +2 more sources