I have training samples of the following shape: (1000,2). These are numeric sequences, each of length = 1000, dimensions = 2.
I need to build a Convolutional Neural Network to output Predictions/Sequences of the same shape (1000, 2). From what I understand, after applying convolution and pooling, the height and width of the input is reduced.
How should I then set up the fully connected layer(s) and an output layer in my CNN, so that the output dimensions match the input dimensions? Or in general, how should I set up my CNN architecture to achieve this?