VGG16 Training new dataset: Why VGG16 needs label to have shape (None,2,2,10) and how do I train mnist dataset with this network?
Low accuracy is caused by the problem in layers. I just modified my network and obtained .7496 accuracy.
I was trying to train CIFAR10 and MNIST dataset on VGG16 network. In my first attempt, I got an error which says shape of input_2 (labels) must be (None,2,2,10). What information does this structure hold in 2x2x10 array because I expect input_2 to have shape (None, 10) (There are 10 classes in both my datasets).
I tried to expand dimensions of my labels from (None,10) to (None,2,2,10). But I am sure this is not the correct way to do it since I obtain a very low accuracy (around 0.09)
(I am using keras, Python3.5)