Table 4.

Model 1, 2, 3 architecture

	Model 1	Model 2	Model 3
Layers	Parameters	Parameters	Parameters
Layer 1—FullyConnected	Input layer	Input layer	Input layer
Layer 2—FullyConnected	30	80	80
Layer 3—FullyConnected	10	70	70
Layer 4—FullyConnected	2	40	50
Layer 5—FullyConnected	–	10	20
Layer 6—FullyConnected	–	2	10
Layer 7- FullyConnected	–		2

The number of layers and the number of neurons in each layer can vary. Moreover, the hyper-parameters can be tuned to improve the final performance. The number of trainable and non-trainable layers can vary, but transfer learning does not perform well if all layers are trainable and the performance is improved