In this paper, we propose a novel convolutional encoder-decoder network with skip connections, named CEDNS, to improve the performance of saliency prediction. The encoder network utilizes the DenseNet ...

We propose a new semantic segmentation method and the necessity of certainty for practical use of semantic segmentation in scene understanding. We implement a deep fully convolutional encoder-decoder ...

For training, download the version of Fairseq-py In the training/ directory, within the preprocess.sh script, place paths to the the training datasets and development datasets. The source and target ...

Based on the classical encoder-decoder framework, our network contains three core strategies: parallel dilated convolutional module, channel attention mechanism and residual connections. The ...

Deep convolutional encoder-decoder networks for uncertainty quantification of dynamic multi-phase flow in heterogeneous random media . uncertainty-quantification time-dependent multi-phase-flows ...