[HTML][HTML] AutoML: A systematic review on automated machine learning with neural architecture search

I Salehin, MS Islam, P Saha, SM Noman, A Tuni… - Journal of Information …, 2024 - Elsevier
Abstract AutoML (Automated Machine Learning) is an emerging field that aims to automate
the process of building machine learning models. AutoML emerged to increase productivity …

A systematic review of optimization algorithms for structural health monitoring and optimal sensor placement

S Hassani, U Dackermann - Sensors, 2023 - mdpi.com
In recent decades, structural health monitoring (SHM) has gained increased importance for
ensuring the sustainability and serviceability of large and complex structures. To design an …

Convolutional neural networks: A survey

M Krichen - Computers, 2023 - mdpi.com
Artificial intelligence (AI) has become a cornerstone of modern technology, revolutionizing
industries from healthcare to finance. Convolutional neural networks (CNNs) are a subset of …

Joint secure offloading and resource allocation for vehicular edge computing network: A multi-agent deep reinforcement learning approach

Y Ju, Y Chen, Z Cao, L Liu, Q Pei… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
The mobile edge computing (MEC) technology can simultaneously provide high-speed
computing services for multiple vehicular users (VUs) in vehicular edge computing (VEC) …

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 …

Deep transfer learning approaches for Monkeypox disease diagnosis

MM Ahsan, MR Uddin, MS Ali, MK Islam… - Expert Systems with …, 2023 - Elsevier
Monkeypox has become a significant global challenge as the number of cases increases
daily. Those infected with the disease often display various skin symptoms and can spread …

[PDF][PDF] Comparison of optimization techniques based on gradient descent algorithm: A review

SH Haji, AM Abdulazeez - PalArch's Journal of Archaeology of …, 2021 - researchgate.net
Whether you deal with a real-life issue or create a software product, optimization is
constantly the ultimate goal. This goal, however, is achieved by utilizing one of the …

PSTCNN: Explainable COVID-19 diagnosis using PSO-guided self-tuning CNN

W Wang, Y Pei, SH Wang… - … : official journal of the …, 2022 - pmc.ncbi.nlm.nih.gov
Since 2019, the coronavirus disease-19 (COVID-19) has been spreading rapidly worldwide,
posing an unignorable threat to the global economy and human health. It is a disease …

Analysis of various optimizers on deep convolutional neural network model in the application of hyperspectral remote sensing image classification

S Bera, VK Shrivastava - International Journal of remote sensing, 2020 - Taylor & Francis
Hyperspectral image (HSI) classification is a most challenging task in hyperspectral remote
sensing field due to unique characteristics of HSI data. It consists of huge number of bands …

Survey of optimization algorithms in modern neural networks

R Abdulkadirov, P Lyakhov, N Nagornov - Mathematics, 2023 - mdpi.com
The main goal of machine learning is the creation of self-learning algorithms in many areas
of human activity. It allows a replacement of a person with artificial intelligence in seeking to …