Convolution blocks The batch normalization is the only difference. It is present in the 2018 conference paper. It is absent in the 2019 journal paper. In the 2018 conference paper: Each layer of the ...

In this paper, we propose a dilated convolution network with edge fusion block and directional feature maps for cardiac MRI segmentation. The network uses feature fusion module to preserve boundary ...

Our neural network is composed of four convolution blocks, responsible for learning EEG representations across all target frequencies. The fifth convolution layer is a multi-task learning block, where ...

Trellis Diagram A convolutional code is a state machine. As such, a graph can be constructed called a trellis diagram. This diagram has time across the top and bit states along the side.

The improved U_net algorithm based on mixed convolution blocks (McbUnet), which combines the advantages of U-Net and residual learning, is proposed for cell image segmentation in this paper. The ...

Deep convolutional neural networks have achieved remarkable progress in recent years. However, the large volume of intermediate results generated during inference poses a significant challenge to the ...