In the initial stage, endmember extraction and abundance map estimation are carried out using a convolutional autoencoder. An elliptical kernel is then applied to compute spectral distances and ...

To overcome these challenges, we propose a novel LCVAE-CNN methodology that integrates a Location-Conditioned Variational Autoencoder (LCVAE) and a multi-task Convolutional Neural Network (CNN) to ...

It uses an LSTM (Long Short-Term Memory) autoencoder model built with TensorFlow/Keras to learn normal patterns from your metrics and identify deviations. The system includes scripts for data ...

Mind-wandering reflects a dynamic interplay between focused attention and off-task mental states ... processes of continuous sensory sequences using our previously proposed variational RNN model under ...