Retrieval of soil salinity from Sentinel-2 multispectral imagery

MM Taghadosi, M Hasanlou… - European Journal of …, 2019 - Taylor & Francis
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 …

PSDCE: Physiological signal-based double chaotic encryption for instantaneous E-healthcare services

J Wang, D Huang, S Fan, K Han, G Jeon… - Future Generation …, 2023 - Elsevier
As fundamental technical support to instantaneous E-healthcare services, Wireless Body
Area Networks (WBANs) have attracted huge attention in the scientific and industrial …

Feature-ensemble-based novelty detection for analyzing plant hyperspectral datasets

A AlSuwaidi, B Grieve, H Yin - IEEE Journal of Selected Topics …, 2018 - ieeexplore.ieee.org
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 …

Utilising grassland management and climate data for more accurate prediction of herbage mass using the rising plate meter

DJ Murphy, P Shine, BO Brien, MO Donovan… - Precision …, 2021 - Springer
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 …

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 …

[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 …

Multi-label feature selection using q-rung orthopair hesitant fuzzy MCDM approach extended to CODAS

S Kavitha, J Satheeshkumar, T Amudha - Mathematics and Computers in …, 2024 - Elsevier
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 …

[HTML][HTML] Process-monitoring-for-quality—A machine learning-based modeling for rare event detection

CA Escobar, R Morales-Menendez, D Macias - Array, 2020 - Elsevier
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 …

Predicting the martensite content of metastable austenitic steels after cryogenic turning using machine learning

M Glatt, H Hotz, P Kölsch, A Mukherjee, B Kirsch… - … International Journal of …, 2021 - Springer
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 …