caffe
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ddtm
Caffe: a fast open framework for deep learning.
It seems the code doesn't work. I follow the instrucment as the readme file but the loss is unchanged(dc_loss is almost 0.69+-, lp_loss is almost 3.36+-). What's wrong with that?
It seems that the reverse validation (rv) approach (as mentioned in the paper) to hyper-parameter selection has not been carried out in the repository. So I wanted to ask some...
Hello, I am trying to reproduce the results from your ICML 2015 paper. I have installed caffe and pycaffe from your forked version of it, and run the prepare_experiments scripts....
Where is the following script ? ./examples/adaptation/experiments/amazon_to_webcam/scripts/train.sh
after run the prepare_experiments.sh,i get two folders:datasets and experiments. but the datasets is empty,and i am pretty sure i have change the path... i am so confused..... can anyone tell...
Hi, I am trying to use your concept for adapting a semantic segmentor (FCN). But I found that after the error rate of the domain classifier began to increase, the...
Hi, Since there are 2 domain labels, the layer connected to SigmoidCrossEntropyLoss shouldnt be 2 instead of 1? please, see here: https://github.com/ddtm/caffe/blob/grl/examples/adaptation/protos/train_val.prototxt#L654
Can anybody confirm what accuracy they are getting using this code in all the 3 experiments.
