Cifar-10 object recognition challenge with simple CNN (89% accuracy after 100 epochs). Techniques that helped increase accuracy (77%->89%):-
- Adding dropout layers
- Increasing the dropout value as we approach the final layer
- Adding batch-normalisation
- Training for a large number of epochs( Was initially training for 50 epochs)
- Using data augmentation
Notebook 2 - Uses Transfer Learning (Resnet-34) achieves about ~91% accuracy