Although many machine learning (ML) and, more recently, deep learning (DL) solutions have been developed to address this issue, most fail to strike an effective balance between speed and performance.

In this paper, a feature learning method using a stacked contractive autoencoder (sCAE) is presented to extract ... Experiment results show that our deep learning model can separate nonlinear noise ...

and that the methods of directly extracting current signal features using deep learning algorithms have insufficient feature extraction, a new series arc fault detection method based on denoising ...

Autoencoders (AEs) are unsupervised learning models that automatically extract data features from large datasets. With advancements in deep learning technology ... improving the model's performance.

In this paper, we suggested a novel data-driven PI method for TEAM treatment using emerging bioinformatics techniques in combination with feature extraction using a deep autoencoder, one of the ...