I am trying to replicate the network described in this paper in Figure 3 (A). https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2020.00251/full "(A) CNN model displaying input, convolution with pooling layers, and hidden-unit layers. The first two layers perform the convolution, the Rectified Linear Units (ReLU) function and the pooling processes for feature extraction. The last two layers with 128 and 64 hidden nodes perform the class classification in HC or ADHD." I am new to python and struggling with the first two convolutional layers. Is patch size just another way to say kernel? How do I set the frequency parameters for the second convolutional layer? Continue reading...
