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Convolution Neural Network architecture. Conv 1 is the first 1-D Convolution layer with 64 filters of size 2, followed by a Max-Pool layer (Max-Pool1) with a pool size of 2, stacked with a second block of 1-D Convolutional layer (Conv 2) and Max-Pool layer (Max-Pool2), followed by a flatten layer, a fully connected layers with 32 neuron units and the output layer with sigmoid activation function.
