This SegNet based Convolutional Encoder-Decoder network can be used for unsupervised feature learning for particular datasets. The PyTorch Dataset class for the MICCAI dataset has been provided. You ...

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 ...

Conv-TasNet is a recently proposed waveform-based deep neural network that achieves state-of-the-art performance in speech source separation. Its architecture consists of a learnable encoder/decoder ...

Depth estimation from a single image is a fundamental problem in the field of computer vision. With the great success of deep learning techniques, various self-supervised monocular depth estimation ...

Our proposed model uses a variant of the graph attention network (GAT) as the encoder and uses variants of ConvE [Conv-TransE (Shang et al., 2019), Conv-TransR] as decoder, to achieve the simultaneous ...

Conv-TasNet is a recently proposed waveform-based deep neural network that achieves state-of-the-art performance in speech source separation. Its architecture consists of a learnable encoder/decoder ...