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Retrieval of soil salinity from Sentinel-2 multispectral imagery
Soil salinity is a widespread environmental hazard and the main causes of land degradation
and desertification, especially in arid and semi-arid regions. The first step in finding such a …
and desertification, especially in arid and semi-arid regions. The first step in finding such a …
PSDCE: Physiological signal-based double chaotic encryption for instantaneous E-healthcare services
As fundamental technical support to instantaneous E-healthcare services, Wireless Body
Area Networks (WBANs) have attracted huge attention in the scientific and industrial …
Area Networks (WBANs) have attracted huge attention in the scientific and industrial …
Feature-ensemble-based novelty detection for analyzing plant hyperspectral datasets
Recently, there has been a significant increase in the use of proximal or remote
hyperspectral imaging systems to study plant properties, types, and conditions. Numerous …
hyperspectral imaging systems to study plant properties, types, and conditions. Numerous …
Utilising grassland management and climate data for more accurate prediction of herbage mass using the rising plate meter
Efficient grass-based livestock production depends on precise allocation of pasture to the
herd in the form of herbage mass (HM). Accurate measurement of HM results in increased …
herd in the form of herbage mass (HM). Accurate measurement of HM results in increased …
New filter approaches for feature selection using differential evolution and fuzzy rough set theory
E Hancer - Neural Computing and Applications, 2020 - Springer
Nowadays the incredibly advanced developments in information technologies have led to
exponential growth in the datasets with respect to both the dimensionality and the sample …
exponential growth in the datasets with respect to both the dimensionality and the sample …
[КНИГА][B] Machine Learning in Manufacturing: Quality 4.0 and the Zero Defects Vision
CA Escobar, R Morales-Menendez - 2024 - books.google.com
Machine Learning in Manufacturing: Quality 4.0 and the Zero Defects Vision reviews
process monitoring based on machine learning algorithms and the technologies of the fourth …
process monitoring based on machine learning algorithms and the technologies of the fourth …
Multi-label feature selection using q-rung orthopair hesitant fuzzy MCDM approach extended to CODAS
This work addresses the issue of multi-label feature selection by extending the CODAS
technique with a q-rung orthopair hesitant fuzzy multi-criteria decision-making approach …
technique with a q-rung orthopair hesitant fuzzy multi-criteria decision-making approach …
[HTML][HTML] Process-monitoring-for-quality—A machine learning-based modeling for rare event detection
Abstract Process Monitoring for Quality is a Big Data-driven quality philosophy aimed at
defect detection through binary classification and empirical knowledge discovery. It is …
defect detection through binary classification and empirical knowledge discovery. It is …
Predicting the martensite content of metastable austenitic steels after cryogenic turning using machine learning
During cryogenic turning of metastable austenitic stainless steels, a deformation-induced
phase transformation from γ-austenite to α'-martensite can be realized in the workpiece …
phase transformation from γ-austenite to α'-martensite can be realized in the workpiece …