This model helps us classify 10 different real-life objects by undergoing training under tensorflow's CIFAR dataset which contains 60,000 32x32 color images with 6000 images of each class. I have made use of a stack of Conv2D and MaxPooling2D layers followed by a few densely connected layers. Following are the 10 different real-life objects that this model can classify:
- Airplane
- Automobile
- Bird
- Cat
- Deer
- Dog
- Frog
- Horse
- Ship
- Truck