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Hi, thank you for your work.
Do you have any suggestions on this behavior ?
I ran the training for the classificator (without GAIN) the minimal amount of iterations just to have a snapshot of the model, same with GAIN (I've tried to use the previously pretrained model, and also without pretraining, same accuracy, no change).
The accuracy for both with and without GAIN is about 72%, although maybe it is explainable, why the result is the same (not trained enough), but isn't there should be any heating (in the meaning of the heating maps) just with 72% accuracy ?
Is this expected or anomalous behavior ?
I didn't use any pretrained models of FCN8, because I didn't find them available now, so I can look only at those results.
If it is anomalous, what can be the reason, where should I look for the problem for your opinion ?
Thank you in advance, appreciate your help.
The text was updated successfully, but these errors were encountered:
Hi, thank you for your work.
Do you have any suggestions on this behavior ?
I ran the training for the classificator (without GAIN) the minimal amount of iterations just to have a snapshot of the model, same with GAIN (I've tried to use the previously pretrained model, and also without pretraining, same accuracy, no change).
The accuracy for both with and without GAIN is about 72%, although maybe it is explainable, why the result is the same (not trained enough), but isn't there should be any heating (in the meaning of the heating maps) just with 72% accuracy ?
Is this expected or anomalous behavior ?
I didn't use any pretrained models of FCN8, because I didn't find them available now, so I can look only at those results.
If it is anomalous, what can be the reason, where should I look for the problem for your opinion ?
Thank you in advance, appreciate your help.
The text was updated successfully, but these errors were encountered: