Table 3. The architectures of networks.

Network	Structure
3D VGG	14 convolutional layers, 1 max-pooling layer, 1 average pooling layer, and 1 fully connected layer
3D ResNet	1 transition layer (consists of a 7×7 convolutional layer and a 2×2 max pooling), 8 residual blocks, 1 average pooling layer, and 1 fully connected layer
3D SE-ResNet	17 convolutional layers, 1 max-pooling layer, 1 average pooling layer, and 15 fully connected layers
3D CA-ResNet	The structure is similar to that of 3D ResNet except that the residual blocks contain 8 coordinate attention blocks

3D, three-dimensional; VGG, visual geometry group; ResNet, residual network; SE-ResNet, squeeze-and-excitation residual network; CA-ResNet, coordinate attention residual network.