CNNs are specialized deep neural networks for processing ... translation or summarization. The encoder processes the input data to form a context, which the decoder then uses to produce the output.

We investigate the ability of neural-network surrogate models ... While simple feedforward networks are used for one-dimensional (1D) Poisson equation, an encoder-decoder architecture with a ...

To this end, we introduce, a multi-scale encoder-decoder self-attention ... we facilitate a deep neural network architecture that learns both macro-level and micro-level dependencies between ...

Semantic segmentation of mitochondria from electron microscopy (EM) images is an essential ... we develop a hierarchical encoder-decoder network (HED-Net), which has a three-level nested U-shape ...

In brief, RNN models and LSTM models consist of encoder and decoder networks that analyze input ... but for now let’s take a look at the architecture of a transformer neural network at a higher level.