Figure 10

Original architecture for this study. The architecture consisted of total of eight layers of two dimensional convolution. The figures under each convolution layer indicate the size (height and width) and number of future maps and layers. “Conv2D” refers to 2-dimentional convolution. “BatchNorm” refers to batch normalization. “SE block” refers to Squeeze-and-Excitation block.