This study proposes a method that uses a deep denoising autoencoder to filter out various levels of industrial noise from audio data and employs unsupervised learning models for rapid and accurate ...

Exploring deep learning models for medical imaging. A collection of Jupyter notebooks documenting the learning journey, with new experiment demos added over time.

Algorithms, examples and tests for denoising, deblurring, zooming, dequantization and compressive imaging with total variation (TV) and second-order total generalized variation (TGV) regularization.

Abstract: Industrial process data are usually affected by random and gross errors leading to deviation from the true value and violation of process constraints. Traditional data reconciliation methods ...

Methods: This study integrates rainfall, surface displacement, and vertical displacement monitoring data, and proposes an automatic failure mode identification method based on deep convolutional ...