A PyTorch implementation for paper Unsupervised Domain Adaptation by Backpropagation

deep-learningdomain-adaptationpytorch

You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

Tree: 7ffd03ff34

master

Branches Tags

${ item.name }

Create tag ${ searchTerm }

Create branch ${ searchTerm }

from '7ffd03ff34'

${ noResults }

pytorch-dann-resnet/experiments

History

wogong 7ffd03ff34 fix lr, add relu to the last conv layer, add l2 norm, add dropout. da result to 60%, source only result to 52%.		6 years ago
..
mnist_mnistm.py	rename dann.py to train.py	6 years ago
office.py	rename dann.py to train.py	6 years ago
office31_10.py	rename dann.py to train.py	6 years ago
svhn_mnist.py	rename dann.py to train.py	6 years ago
synsigns_gtsrb.py	fix lr, add relu to the last conv layer, add l2 norm, add dropout. da result to 60%, source only result to 52%.	6 years ago
synsigns_gtsrb_src_only.py	fix lr, add relu to the last conv layer, add l2 norm, add dropout. da result to 60%, source only result to 52%.	6 years ago