CIFAR-10 is an established computer-vision dataset used for object recognition. It is a subset of the 80 million tiny images dataset and consists of 60,000 32x32 color images containing one of 10 object classes, with 6000 images per class. It was collected by Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton.
I am using VGG16 model as Transfer Learning to use Imagenet weights upto 3 layers and build custom layers over that.
Accuracy achieved is more than 0.97 for 40 epochs, can be better for more epochs, but sadly I lack computing power.