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Hi, it‘’s my first time to try domain adaptation. Here is my scenario: i am doing a image classification task, there are already 100k training data with labels (called A), i also can obtain large da…
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首先,感谢作者贡献这样一个精致的仓库,让不懂神经网络的我得以在短时间内快速入门迁移学习!但是我还是有一些小小的建议:
文章adversarial discriminative domain adaptation应该也算是unsupervised domain adaptation中几个富有盛名的算法之一,我发现DeepDA似乎没有关于其的实现以及与其他方法的比较。这感觉不利于大家基于这个仓库来在…
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You had mentioned that the backbone network is ResNet-50 pretrained on Imagenet.
https://github.com/thuml/Universal-Domain-Adaptation/blob/5d7caa95af7e3675305c542253c4e372801897d2/net.py#L37
Bu…
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Dear Sir, greetings. Firstly, congratulations on the successful publication of your paper in NeurIPS. However, I have some minor questions regarding its content that I would like to consult with you. …
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Hi, thanks for sharing your code.
I want to use your DAEL model, but can ADEL support the scene that multi-source with different categories (such as category-shift problem solved in "Deep Cocktail …
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In Table 1 the paper shows very high scores (more than 90%) in the digit classification tasks. So the question is that the testing set is merely the target-domain testing set or the combination of bot…
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Hi author of MOTSYNTH
Can we use real data (e.ge. MOT17) with un-labeled and use unsupervised learning?
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Dear All,
together with my colleagues I have been working over this year on two image processing operations `Feature Distribution Matching` and `Histogram Matching` in multiple color spaces for …
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I got a couple of emails so asking, so, here it is:
In our work "Unsupervised domain adaptation in brain lesion segmentation with adversarial networks" (https://arxiv.org/abs/1612.08894, accepted i…
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I have noticed that most of the UDA experiments on Office 31 or visda provide a train_list.txt and val_list.txt during the dataloader creation stage.
Doesn't providing the list for both source and ta…