A review of principal component analysis algorithm for dimensionality reduction
BMS Hasan, AM Abdulazeez - Journal of Soft Computing …, 2021 - publisher.uthm.edu.my
Big databases are increasingly widespread and are therefore hard to understand, in
exploratory biomedicine science, big data in health research is highly exciting because data …
exploratory biomedicine science, big data in health research is highly exciting because data …
Explainable ai for bioinformatics: Methods, tools and applications
Artificial intelligence (AI) systems utilizing deep neural networks and machine learning (ML)
algorithms are widely used for solving critical problems in bioinformatics, biomedical …
algorithms are widely used for solving critical problems in bioinformatics, biomedical …
A novel combined approach based on deep Autoencoder and deep classifiers for credit card fraud detection
H Fanai, H Abbasimehr - Expert Systems with Applications, 2023 - Elsevier
Due to the growth of e-commerce and online payment methods, the number of fraudulent
transactions has increased. Financial institutions with online payment systems must utilize …
transactions has increased. Financial institutions with online payment systems must utilize …
[HTML][HTML] Spatially autocorrelated training and validation samples inflate performance assessment of convolutional neural networks
Deep learning and particularly Convolutional Neural Networks (CNN) in concert with remote
sensing are becoming standard analytical tools in the geosciences. A series of studies has …
sensing are becoming standard analytical tools in the geosciences. A series of studies has …
A newcomer's guide to deep learning for inverse design in nano-photonics
Nanophotonic devices manipulate light at sub-wavelength scales, enabling tasks such as
light concentration, routing, and filtering. Designing these devices to achieve precise light …
light concentration, routing, and filtering. Designing these devices to achieve precise light …
Advanced intrusion detection combining signature-based and behavior-based detection methods
Recently, devices in real-time systems, such as residential facilities, vehicles, factories, and
social infrastructure, have been increasingly connected to communication networks …
social infrastructure, have been increasingly connected to communication networks …
Attentive transformer deep learning algorithm for intrusion detection on IoT systems using automatic Xplainable feature selection
Recent years have witnessed an in-depth proliferation of the Internet of Things (IoT) and
Industrial Internet of Things (IIoT) systems linked to Industry 4.0 technology. The increasing …
Industrial Internet of Things (IIoT) systems linked to Industry 4.0 technology. The increasing …
An unsupervised approach for health index building and for similarity-based remaining useful life estimation
Predictive maintenance techniques attempt to trigger a maintenance intervention at the right
moment by estimating the life expectation. Predictive maintenance is increasingly …
moment by estimating the life expectation. Predictive maintenance is increasingly …
Integrating autoencoder and heteroscedastic noise neural networks for the batch process soft-sensor design
Viscosity represents a key product quality indicator but has been difficult to measure in-
process in real-time. This is particularly true if the process involves complex mixing …
process in real-time. This is particularly true if the process involves complex mixing …
Monitoring MBE substrate deoxidation via RHEED image-sequence analysis by deep learning
Reflection high-energy electron diffraction (RHEED) is a powerful tool in molecular beam
epitaxy (MBE), but RHEED images are often difficult to interpret, requiring experienced …
epitaxy (MBE), but RHEED images are often difficult to interpret, requiring experienced …