Figure 5.

Training and validation loss for the three architectures trained using the public and the fused datasets. Note that VGG-16 trained on the fused dataset ended after one epoch only, hence there is no corresponding figure. The models are able to properly fit training data and improve with experience (as seen in validation curves).