In the journal paper, there are 3 convolution blocks per scale. The number of convolution blocks per scale are also different in the 2 papers. Contributing. I am welcoming any feedback under the form ...

The convolution kernel of size (2r + 1) 2 is represented by Ω r = [− r, r] 2 ∩ Z 2 and k: Ω r → R. D(⋅) represents the output of the convolution operation, where l represents the dilation rate, s is ...

The fifth convolution layer is a multi-task learning block, where it learns to differentiate multiple SSVEP target frequencies. C1 block was designed to extract the spectral representation of the EEG ...

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 ...

Block Convolution: Toward Memory-Efficient Inference of Large-Scale CNNs on FPGA Abstract: Deep convolutional neural networks have achieved remarkable progress in recent years. However, the large ...