The aim of this research was to develop a deep learning method which involved wavelet transform (WT) and stack convolution auto encoder (SCAE) for extracting compound heavy metals detection deep features of lettuce leaves. WT was used to decompose th...
PURPOSE: Gadoxetic acid uptake rate (k ) obtained from dynamic, contrast-enhanced (DCE) magnetic resonance imaging (MRI) is a promising measure of regional liver function. Clinical exams are typically poorly temporally characterized, as seen in a low...
Metabolomics : Official journal of the Metabolomic Society
Jan 21, 2020
INTRODUCTION: Metabolomics data is commonly modelled multivariately using partial least squares discriminant analysis (PLS-DA). Its success is primarily due to ease of interpretation, through projection to latent structures, and transparent assessmen...
BACKGROUND: Viral infectious diseases are the serious threat for human health. The receptor-binding is the first step for the viral infection of hosts. To more effectively treat human viral infectious diseases, the hidden virus-receptor interactions ...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Dec 23, 2019
Identification and development of salinity tolerant genotypes and varieties are one of the promising ways to improve productivity of salt-affected soils. Alternate methods to achieve this are required as the conventional methods are time-consuming an...
The method of 3D fluorescence spectroscopy combined with convolutional neural network (CNN) was developed to identify the counterfeit sesame oil. AlexNet, a pre-trained CNN architecture, was transferred to extract spectral characteristics. Then these...
Untargeted steroid identification represents a great analytical challenge even when using sophisticated technology such as two-dimensional gas chromatography coupled to high resolution mass spectrometry (GC × GCHRMS) due to the chemical similarity of...
Metabolomics : Official journal of the Metabolomic Society
Oct 18, 2019
BACKGROUND: Metabolomics data, with its complex covariance structure, is typically modelled by projection-based machine learning (ML) methods such as partial least squares (PLS) regression, which project data into a latent structure. Biological data ...
In this work, the use of design of experiments and posterior data modelling by artificial neural network (ANN) and least squares (LS) is presented as a suitable analytical tool for the performance optimization of a tandem mass spectrometric detector ...
Dual-energy computed tomography (DECT) imaging plays an important role in advanced imaging applications due to its material decomposition capability. Image-domain decomposition operates directly on CT images using linear matrix inversion, but the dec...
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