Several dimensionality reduction techniques were applied to hyperspectral reflectance
images of wine grape berries, leading a study of the machine learning models' efficiency in …

Total hatching egg set (for both egg production chicks and broilers) in the Agriculture and
Agri-Food Canada report 2017 was over 1.0 billion. With the fertility rate for this year …

Multispectral and hyperspectral feature spaces are useful for a variety of remote sensing
applications ranging from spectral mixture modeling to discrete thematic classification. In …

In this paper, we analyze the current state of the discrete theory of radiative transfer. One-
dimensional, three-dimensional and stochastic radiative transfer models are considered. It is …

In atmospheric science we are confronted with inverse problems arising in applications
associated with retrievals of geophysical parameters. A nonlinear mapping from geophysical …

In this paper, we present neural network methods for predicting uncertainty in atmospheric
remote sensing. These include methods for solving the direct and the inverse problem in a …

Current atmospheric composition sensors provide a large amount of high spectral resolution
data. The accurate processing of this data employs time-consuming line-by-line (LBL) …

A spectral acceleration approach for the spherical harmonics discrete ordinate method
(SHDOM) is designed. This approach combines the correlated k-distribution method and …

Medical healthcare systems are being extensively studied, giving computer technology lots
of space to innovate. The most important medical research is predicting cancer, which may …

The objective of the present work is to describe a technique to approximate atmospheric
path transmissivities using a recurrent structure, following a method proposed recently but …