This paper proposes a novel approach for driving chemometric analyses from spectroscopic
data and based on a convolutional neural network (CNN) architecture. For such purpose …

In this article, we examine Independent Component Analysis (ICA) and the concept of
Mutual information (MI) as a quantitative measure of independence from the point of view of …

In industrial processes, long short-term memory (LSTM) is usually used for temporal
dynamic modeling of soft sensor. The process data usually have various temporal …

A PLS-bootstrap-VIP approach is proposed as a simple wavelength selection method, yet
having the ability to identify relevant spectral intervals. This approach is particularly attractive …

Sensors have been widely used for disease diagnosis, environmental quality monitoring,
food quality control, industrial process analysis and control, and other related fields. As a key …

Near infrared (NIR) spectroscopy combined with multivariate analysis were attempted to
determine freshness of eggs. Independent component analysis (ICA) and principle …

Three effective wavelength (EW) selection methods combined with visible/near infrared
(Vis/NIR) spectroscopy were investigated to determine the soluble solids content (SSC) of …

Two sensitive wavelength (SWs) selection methods combined with visible/near-infrared
(Vis/NIR) spectroscopy were investigated to determine the soluble solids content (SSC) and …

Abstract Support Vector Machines (SVMs) is known to be a powerful nonparametric
classification technique even for high-dimensional data. Although predictive ability is …

The large number of spectral bands acquired by hyperspectral imaging sensors allows us to
better distinguish many subtle objects and materials. Unlike other classical hyperspectral …