We propose a Wavelet based Deep Emotion Recognition (WaDER) method using an autoencoder and 1D convolutional neural network (CNN) and long short-term memory (LSTM) networks. The autoencoder is used to ...

If the CEO of a soda company declared that soda-making technology is getting so good it’s going to ruin the global economy, you’d be forgiven for thinking that person is either lying or fully ...

On Thursday, Anthropic CEO Dario Amodei warned on CNN that the technology will spike unemployment sooner than political leaders and businesses expect — and they aren’t ready for it.

Before discussing the architecture itself, let's provide a detailed description of the layers used: autoencoder LSTM, 1D-CNN, and transformer. The following subsections explain how each layer is used ...

The 1D CNN then captures spatial features through layers of 1D convolutions, max-pooling, and dropout, effectively analyzing the one-dimensional time-series patterns of the interferogram. The main ...

When the autoencoder processes a 3D matrix of size 128 3, it is flattened into a 1D array of length (2097152) as input. Both the encoding and decoding phases featured two fully connected layers, with ...