I have a dataset of 34k (200x200) images and I want to build an 8 class age detector.
I've tried a lot of different networks design, regularizations, dropout layers, grayscale images, data augmentation on the training set, learning rate, shuffle the data order etc... but I only get accuracy from 43% to 48%. I've also tried some famous networks as AlexNet or LeNet-5 but the maximum accuracy I can get is about 49%.
In such a task I would expect an accuracy similar to what a human can get or at least something about 80-85%. What can be the reason for such a low accuracy? What could I try?