Table 2.

Schematic of the proposed CNN architecture. The input size is given in each row. The output size is the input size of the next row. All convolutions were performed with sigmoid activation and 40% dropout.

Layer	Kernel size / Remarks	Input Size
Conv.	3×3 / ‘same’	11×11×128
Conv.	3×3 / ‘same’	11×11×64
Conv.	3×3 / ‘same’	11×11×92
Avg. Pool	3×3 / ‘valid’	11×11×128
Linear	Flatten	9×9×128
Fully-Conn.	-	1×10368
Linear	Logits	1×1000
Softmax	Classifier	1×4