I was wondering if it’s possible, since all the examples I found online use convnets. I am trying to get an ok accuracy (say 90%) with just a feedforward net and no convolutions.
I know the convnet is the way to go, but I am still curious.
For example, even the pytorch tutorial uses a convnet for MNIST, but I can get around 97% accuracy in it with a feedforward without convolutions.
So far however, for CIFAR10 I’m only achieving 28 to 30% accuracy with the following setup: (linear = linear combination plus bias)

linear(32323, 300), ReLU
linear(300, 200), ReLU
linear(200, 100), ReLU
linear(100, 50), ReLU
linear(50, 10), Softmax
. Cross Entropy Loss