Closed quangnguyenbn99 closed 6 years ago
Hi @NathanielNguyen11 ,
In my machine, the converged loss is about 3.4 too. And, the converged loss is about 1.2 in the original matconvNet implement. I am trying to find why, but it may be slow since I have something else having to do. If you find the reason, welcome to pull a request.
thanks.
i changed the activation function in layer which is originally relu to leaky relu, and the loss converges to about 1.2. Hope that helps you~ @crisb-DUT
Hi, I am trying to train this model using my own noise data but i am seeing same issue. Even after running for 12hrs on GPU but final error came to only 3 with Adamoptimser and 2.5 using AdamDelta optimiser. Please suggest if you the actual error. As it is mentioned that chnage relu to leaky-relu to get error of 1. But is it sufficient to get performance comparable to matlab performance with such trained model. Regards, Sumit Jha
Thanks @edogawachia. I will have a try if there is any free time.
@NathanielNguyen11 I noticed that the last conv layer don't use BN and relu in paper, and I changed the code so the training loss decreased less than 1.2.
Thanks @lizhiyuanUSTC ,
You are right. I have merged your pull request. Now I am training the new model.
Hi all,
I have trained and tested the new model, and it has the same Gaussian denoising performance at noise level 25 on BSD68 test set.
Thanks for all of your help.
Dear Mr/Mrs
I am kindly considering about the loss parameter of the code. The later only stops from 3.4 to 3.6, then it doesn't decrease to around 0 . Hence, I write this topic to give a question that: " am I running the code correctly?" I am so sorry that if my stupid question disturb you. Thank for your attention very much.