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[HTML][HTML] AutoML: A systematic review on automated machine learning with neural architecture search
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 …
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
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 …
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 …
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
The mobile edge computing (MEC) technology can simultaneously provide high-speed
computing services for multiple vehicular users (VUs) in vehicular edge computing (VEC) …
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
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 …
a patient affected with a tumor is difficult to determine because they are infrequent and …
Deep transfer learning approaches for Monkeypox disease diagnosis
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 …
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
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 …
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 …
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
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 …
sensing field due to unique characteristics of HSI data. It consists of huge number of bands …
Survey of optimization algorithms in modern neural networks
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 …
of human activity. It allows a replacement of a person with artificial intelligence in seeking to …