Table 3.

Architecture of our CNN model and parameter details for each layer utilized in our proposed method.

Type of Layer	Output Shape	Number of Parameters
Input_1 (InputLayer)	[(None, 1024)]	0
tf.reshape (TFOpLambda)	(None, 1024, 1)	0
conv1d (Conv1D)	(None, 1022, 256)	1024
conv1d_1 (Conv1D)	(None, 1020, 128)	98,432
flatten (Flatten)	(None, 130,560)	0
dense_2 (Dense)	(None, 10)	1,305,610
Total:		1,405,066
Trainable:		1,405,066
Non-trainable:		0