Novel manipulations of the well-established multivariate calibration models namely; partial least square regression (PLSR) and support vector regression (SVR) are introduced in the presented comparative study. Two preprocessing methods comprising fir...
PURPOSE: This prospective clinical study assesses the feasibility of training a deep neural network (DNN) for intravoxel incoherent motion (IVIM) model fitting to diffusion-weighted MRI (DW-MRI) data and evaluates its performance.
The pelvis is consistently regarded as the most sexually dimorphic region of the human skeleton, and methods for sex estimation with the pelvic bones are usually very accurate. In this investigation, population-specific osteometric models for the ass...
PURPOSE: To apply an artificial neural network (ANN) for fast and robust quantification of the oxygen extraction fraction (OEF) from a combined QSM and quantitative BOLD analysis of gradient echo data and to compare the ANN to a traditional quasi-New...
Detection of moving object from a visual sequence plays a vital role for the tracking of object. The main objective of this proposed work is to detect and classify the various video sequences with the help of different classification algorithms. The ...
International journal of pharmaceutics
Jun 25, 2019
This work proposes the application of artificial neural networks (ANN) to non-destructively predict the in vitro dissolution of pharmaceutical tablets from Process Analytical Technology (PAT) data. An extended release tablet formulation was studied, ...
Kernel regression models have been used as non-parametric methods for fitting experimental data. However, due to their non-parametric nature, they belong to the so-called "black box" models, indicating that the relation between the input variables an...
Neural networks : the official journal of the International Neural Network Society
May 29, 2019
Recently, the echo state networks (ESNs) have been widely used for time series prediction. To meet the demand of actual applications and avoid the overfitting issue, the online sequential ESN with sparse recursive least squares (OSESN-SRLS) algorithm...
Preparative biochemistry & biotechnology
May 27, 2019
To overcome the problem that soft-sensing model cannot be updated with the bioprocess changes, this article proposed a soft-sensing modeling method which combined fuzzy c-means clustering (FCM) algorithm with least squares support vector machine theo...
High-accuracy and fast detection of nutritive elements in traditional Chinese medicine (PN) is beneficial for providing useful assessment of the healthy alimentation and pharmaceutical value of PN herbs. Laser-induced breakdown spectroscopy (LIBS) w...
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