A couple of other things to try:

Reduce the learning rate by one or more orders of magnitude.
Set the dropout rate to zero (That is: don’t have any dropout).

From what I understand, dropout becomes relevant when the training accuracy grows significantly larger than the test accuracy. If you have trouble increasing the training accuracy, then having a dropout layer may not help.