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Hi, I notice your algorithm is using last conv gradient times the last conv output and go through a relu function to calculate the heatmap. I don't understand why you do this but after a quick scan of the paper, I feel using the gradient of last conv layer rule is more reasonable.
I changed: "last_conv_layer = model.get_layer("conv_pw_13")" to "last_conv_layer = model.get_layer("conv_pw_13_relu") "
and remove "heatmap = np.maximum(heatmap, 0)"
But doing this, the output is more accurate to me.
The text was updated successfully, but these errors were encountered:
Hi, I notice your algorithm is using last conv gradient times the last conv output and go through a relu function to calculate the heatmap. I don't understand why you do this but after a quick scan of the paper, I feel using the gradient of last conv layer rule is more reasonable.
I changed: "last_conv_layer = model.get_layer("conv_pw_13")" to "last_conv_layer = model.get_layer("conv_pw_13_relu") "
and remove "heatmap = np.maximum(heatmap, 0)"
But doing this, the output is more accurate to me.
The text was updated successfully, but these errors were encountered: