From 3aa8b9b47965998f9bf9ee34bc2d8dc3498d45f7 Mon Sep 17 00:00:00 2001 From: wogong Date: Thu, 5 Sep 2019 17:02:35 +0800 Subject: [PATCH] update readme. --- README.md | 15 +++++++++------ 1 file changed, 9 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index 4456a6b..f2df47d 100644 --- a/README.md +++ b/README.md @@ -14,12 +14,15 @@ A PyTorch implementation for paper *[Unsupervised Domain Adaptation by Backpropa ## Note -- `Config()` 为针对特定任务的配置参数 -- `MNISTmodel()` 完全按照论文中的结构，但是 feature 部分添加了 `Dropout2d()`，实验发现是否添加 `Dropout2d()` 对于最后的性能影响很大。最后实验重现结果高于论文，因为使用了额外的技巧，这里还有值得探究的地方。 -- `SVHNmodel()` 无法理解论文中提出的结构，为自定义结构。最后实验重现结果完美。 -- MNIST-MNISTM: `python mnist_mnistm.py` -- SVHN-MNIST: `python svhn_mnist.py` -- Amazon-Webcam: `python office.py` 由于预训练网络的问题，无法复现 +- `MNISTmodel()` + - basically the same network structure as proposed in the paper, expect for adding dropout layer in feature extractor + - large gap exsits between with and w/o dropout layer + - better result than paper +- `SVHNmodel()` + - network structure proposed in the paper may be wrong for both 32x32 and 28x28 inputs + - change last conv layer's filter to 4x4, get similar(actually higher) result +- `AlexModel` + - not successful, mainly due to the preprain model difference ## Result