Hello,
I have a doubt about using conv2d or conv3d on my problem. I have an array of shape (M, M, N) where each image is formed by M x M pixels and we have N of those.
My question is:


Should I use 2d conv where the channels are the N value (i.e. input shape (batch size, N, M, M)


3d conv net where we start with one channel on a 3D image (i.e. input shape (batch size, 1, M, M, N)


The N images may have shared statistics. Now, I have tried both and the 3D conv net seems to give better results but I am not sure how should I interpret that and maybe it is due to an hyperparameter issue.
Thanks.