A study of CNN and transfer learning in medical imaging: Advantages, challenges, future scope

AW Salehi, S Khan, G Gupta, BI Alabduallah, A Almjally… - Sustainability, 2023 - mdpi.com
This paper presents a comprehensive study of Convolutional Neural Networks (CNN) and
transfer learning in the context of medical imaging. Medical imaging plays a critical role in …

Advances in machine learning and IoT for water quality monitoring: A comprehensive review

I Essamlali, H Nhaila, M El Khaili - Heliyon, 2024 - cell.com
Water holds great significance as a vital resource in our everyday lives, highlighting the
important to continuously monitor its quality to ensure its usability. The advent of the. The …

[HTML][HTML] Robust machine learning algorithms for predicting coastal water quality index

MG Uddin, S Nash, MTM Diganta, A Rahman… - Journal of …, 2022 - Elsevier
Coastal water quality assessment is an essential task to keep “good water quality” status for
living organisms in coastal ecosystems. The Water quality index (WQI) is a widely used tool …

Cloud-based intrusion detection approach using machine learning techniques

H Attou, A Guezzaz, S Benkirane… - Big Data Mining and …, 2023 - ieeexplore.ieee.org
Cloud computing (CC) is a novel technology that has made it easier to access network and
computer resources on demand such as storage and data management services. In …

[HTML][HTML] Marine waters assessment using improved water quality model incorporating machine learning approaches

MG Uddin, A Rahman, S Nash, MTM Diganta… - Journal of …, 2023 - Elsevier
In marine ecosystems, both living and non-living organisms depend on “good” water quality.
It depends on a number of factors, and one of the most important is the quality of the water …

An ensemble learning based intrusion detection model for industrial IoT security

M Mohy-Eddine, A Guezzaz… - Big Data Mining and …, 2023 - ieeexplore.ieee.org
Industrial Internet of Things (IIoT) represents the expansion of the Internet of Things (IoT) in
industrial sectors. It is designed to implicate embedded technologies in manufacturing fields …

[PDF][PDF] A Lightweight Hybrid Intrusion Detection Framework using Machine Learning for Edge-Based IIoT Security.

A Guezzaz, M Azrour, S Benkirane… - Int. Arab J. Inf …, 2022 - ccis2k.org
Due to the development of cloud computing and Internet of Things (IoT) environments, such
as healthcare systems, telecommunications and Industry 4.0 or Industrial IoT (IIoT) many …

Prediction of potentially toxic elements in water resources using MLP-NN, RBF-NN, and ANFIS: a comprehensive review

JC Agbasi, JC Egbueri - Environmental Science and Pollution Research, 2024 - Springer
Water resources are constantly threatened by pollution of potentially toxic elements (PTEs).
In efforts to monitor and mitigate PTEs pollution in water resources, machine learning (ML) …

[HTML][HTML] Water quality prediction based on machine learning and comprehensive weighting methods

X Wang, Y Li, Q Qiao, A Tavares, Y Liang - Entropy, 2023 - mdpi.com
In the context of escalating global environmental concerns, the importance of preserving
water resources and upholding ecological equilibrium has become increasingly apparent …

New generation neurocomputing learning coupled with a hybrid neuro-fuzzy model for quantifying water quality index variable: A case study from Saudi Arabia

MS Manzar, M Benaafi, R Costache, O Alagha… - Ecological …, 2022 - Elsevier
Ensuring availability in terms of quality and quantity and sustainable management of safe,
affordable drinking water is one of the integral parts of envisioning the 2030 Sustainable …