Table 3.

Hyper-parameters and value ranges

	Hyper-parameters to optimize	Value ranges
1	Number of Convoluiton layer	[1, 2, 3, 4, 5, 6, 7, 8]
2	Number of Maxpooling layer	[1, 2, 3, 4, 5, 6, 7, 8]
3	Number of FC layers	[1, 2, 3, 4]
4	Number of filters	[16, 24, 32, 48, 64, 96]
5	Filter sizes for conv and pooling	[2, 3, 4, 5, 6, 7]
6	Padding	[0, 1, Same]
7	Stride	[1, 2, 3]
8	L2 regularization	[0.0001, 0.0005, 0.001, 0.005]
9	Momentum	[0.70, 0.75, 0.80, 0.85, 0.9, 0.95]
10	Mini-batch size	[8, 16, 32, 64, 128]
11	Learning rate	[0.0001, 0.0003, 0.0005, 0.001, 0.003, 0.005]
12	Activation function	ReLu, Leaky Relu, ELU, SELU