Customized convolutional neural neworks trained with CIFAR-10 dataset.

Architecture:

• Use 64 11*11 filters for the first convolutional layer.
• followed by 2*2 max pooling layer (stride of 2).
• The next two convolutional layers use 128 3*3 filters followed by the ReLU activation function.
• batch normalization layers added right after each convolutional layers.