So i'm using a dataset with 400 images at the moment (looking to add more in the close future), but meanwhile I was trying to find which CNN architectures is the best between the pretrained network from Deep Learning Toolbox.
So i did some test, to compare them with the same parameters, and for exemple, after 10 epoch I have over 95% for validation accuracy for DenseNet, Inceptionv3 or Xception, but I've under 20% for Darknet, VGG, or GoogleNet. Why is there so much of a difference? Is this because my dataset doesn't have enough image? Not enough epochs?