The applications of machine learning techniques in medical data processing based on distributed computing and the Internet of Things

S Aminizadeh, A Heidari, S Toumaj, M Darbandi… - Computer methods and …, 2023 - Elsevier
Medical data processing has grown into a prominent topic in the latest decades with the
primary goal of maintaining patient data via new information technologies, including the …

[HTML][HTML] IoT for smart cities: Machine learning approaches in smart healthcare—A review

TM Ghazal, MK Hasan, MT Alshurideh, HM Alzoubi… - Future Internet, 2021 - mdpi.com
Smart city is a collective term for technologies and concepts that are directed toward making
cities efficient, technologically more advanced, greener and more socially inclusive. These …

Transfer learning-motivated intelligent fault diagnosis designs: A survey, insights, and perspectives

H Chen, H Luo, B Huang, B Jiang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Over the last decade, transfer learning has attracted a great deal of attention as a new
learning paradigm, based on which fault diagnosis (FD) approaches have been intensively …

Deep learning models for cloud, edge, fog, and IoT computing paradigms: Survey, recent advances, and future directions

S Ahmad, I Shakeel, S Mehfuz, J Ahmad - Computer Science Review, 2023 - Elsevier
In recent times, the machine learning (ML) community has recognized the deep learning
(DL) computing model as the Gold Standard. DL has gradually become the most widely …

A robust approach for brain tumor detection in magnetic resonance images using finetuned efficientnet

HA Shah, F Saeed, S Yun, JH Park, A Paul… - Ieee …, 2022 - ieeexplore.ieee.org
A brain tumor is a disorder caused by the growth of abnormal brain cells. The survival rate of
a patient affected with a tumor is difficult to determine because they are infrequent and …

Multi-classification of brain tumor MRI images using deep convolutional neural network with fully optimized framework

E Irmak - Iranian Journal of Science and Technology …, 2021 - Springer
Brain tumor diagnosis and classification still rely on histopathological analysis of biopsy
specimens today. The current method is invasive, time-consuming and prone to manual …

Deep learning for safe autonomous driving: Current challenges and future directions

K Muhammad, A Ullah, J Lloret… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Advances in information and signal processing technologies have a significant impact on
autonomous driving (AD), improving driving safety while minimizing the efforts of human …

Review of deep learning: concepts, CNN architectures, challenges, applications, future directions

L Alzubaidi, J Zhang, AJ Humaidi, A Al-Dujaili… - Journal of big Data, 2021 - Springer
In the last few years, the deep learning (DL) computing paradigm has been deemed the
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …