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 ...

Neural encoding is the study of how neurons represent information with electrical activity (action potentials) at the level of individual cells or in networks of neurons. Studies of neural ...

These applications typically involve the exchange of small information blocks. Convolutional codes (CC) exhibit near-optimal performance when encoding short blocks. To enable packet-based ...

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 ...

Due to a production error, there was an error regarding the affiliation for Somayeh Makouei. Instead of having affiliation 2, they should have affiliation 1 ...

This is an autoencoder with cylic loss and coding parsing loss for image compression and reconstruction. Network backbone is simple 3-layer fully conv (encoder) and symmetrical for decoder. Finally it ...