Implementation of the LeNet-5 deep neural network model.
Specs
Input Image is 28x28x1 and converted to 32x32x1 as per LeNet requirements.
Convolution layer 1: The output shape should be 28x28x6.
Activation 1: Your choice of activation function.
Pooling layer 1: The output shape should be 14x14x6.
Convolution layer 2: The output shape should be 10x10x16.
Activation 2: Your choice of activation function.
Pooling layer 2: The output shape should be 5x5x16.
Flatten layer: Flatten the output shape of the final pooling layer such that it's 1D instead of 3D.
Fully connected layer 1: This should have 120 outputs.
Activation 3: Your choice of activation function.
Fully connected layer 2: This should have 10 outputs.
Return the result of the 2nd fully connected layer from the LeNet function.