Connection between RNN and Encoder-Decoder: Sequential Processing: Both the encoder and decoder in the Encoder-Decoder architecture are typically implemented using RNNs (or it's variants like LSTM or ...

Recurrent Neural Network (RNN) Model: Creates an encoder-decoder architecture using GRU layers. The encoder processes the input text and generates a context vector. The decoder generates the output ...

In image segmentation by deep learning, encoder-decoder Convolutional Neural Network (CNN) architectures are fundamental for creating and learning representations. However, with many filters in these ...

Neural networks (NNs) and graph signal processing have emerged as important actors in data-science applications dealing with complex (non-linear, non-Euclidean) datasets. In this work, we introduce a ...