… , strided, or transposed convolutions. In this work, we focus on the design of a streaming
convolution engine, called LazyDCstream, that is tuned for dilated convolution. LazyDCstream …

… Compared with regular convolutions, dilated convolutions can … However, the dilated
convolutions feature heavy computation … of the dilated convolutions with different dilation rates are …

… In this study, we set dilated convolution layers in baseline ResNet-50 architecture with
dilation rate 1 … The mathematical formula for dilated convolution layers is shown in Equation 1. …

… flow transformation to convert a dilated convolution to a non-dilated convolution to remove
such need … We analyse real-time samples streamed through multilayer temporal convolutions. …

… , dilated CNN, … dilation rate and the number of layers of dilated convolution to the experimental
results, and find that expanding the number of covered frames or enlarging the dilation …

… architecture able to perform 2D dilated convolutions and suitable for the integration within …
DDR memory and stream them towards the DCE. In turn, the latter streams out the computed …

… We use a two-stream network to extract the spectral information of the MS images and the
spatial information of PAN images, which is helpful for the network to fully learn the correlation …

… performance for a given piece of music using progressively dilated convolutional neural
networks. Our method incorporates varying dilation rates at different layers to capture both short-…

… Here, long short-term memory fused quantum dilated convolutional neural network (LSTM-…
merging deep LSTM (DLSTM) with quantum dilated convolutional neural network (QDCNN). …

… network mainly consisting of dilated convolutions and multi-scale convolutions captures rich
… Finally, the fine-tuning unit fuses the features extracted by the two-stream to complete the …