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This repository has been archived by the owner on Sep 9, 2024. It is now read-only.
Hi,
I am testing Li's 3D CNN network on IndianPines dataset. In table III in disjoint mode, you have an accuracy of 75%. I can't reach more than 65%.
Are the default parameters of the network (lr = 0.01, epoch = 200, patch_size = 5, momentum=0.9, weight_decay = 5e-4, n_planes = 16) the ones you have used ? In particular, in the original paper, n_planes = 2
Did you just apply flip_augmentation or also mixture_augmentation or radiation_augmentation ? Even with those it doesn't work.
The other parameters I used : training_sample = 0.9, default batch_size, class_balancing=True
Thank you :)
The text was updated successfully, but these errors were encountered:
Hi,
I am testing Li's 3D CNN network on IndianPines dataset. In table III in disjoint mode, you have an accuracy of 75%. I can't reach more than 65%.
Thank you :)
The text was updated successfully, but these errors were encountered: