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# Welcome to JunYoung's blog | TENT, Continual test-time adaptation(CoTTA) 논문 리뷰
Test time domain adaptation
[https://junia3.github.io/blog/tent](https://junia3.github.io/blog/tent)
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for training domain adaptation from **KITTI to cityscape** dataset what step I need to flow step by step?
1) The first train faster runs with the KITTI dataset.
2) by using those train weights, trai…
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addaの実装を行う。参考サイトは[ここ](https://github.com/jvanvugt/pytorch-domain-adaptation)。
実装後、精度が出るかテスト。
パラメータチューニングをどこで行うかは要検討で、一旦外で実装する。
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Hi! Thank you for the author's sharing!
I met some problem in training source domain. The model of ct2mr and mr2ct w/o adaptation is 0.68 and 0.49 for me, which is slightly different from the pape…
YYinn updated
3 months ago
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https://arxiv.org/pdf/1505.07818.pdf
We introduce a new representation learning approach for domain adaptation, in which data at training and test time come from similar but different distributions…
leo-p updated
7 years ago
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Hi @wasidennis , before trying to combination feature and output space adaptation, i want to exploit the power of feature space adaptation and was trying to implement feature space alone. The feature …
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1.MixStyle Neural Networks for Domain Generalization and Adaptation
2.Domain Generalization with MixStyle
This is confusing to me
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Hi, There maybe be some questions of the "visdac.py", can you check it plz.
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Hi! Thank you for the author's sharing! The code are very well-organized.
However, when training in the CT-MR domain adaptation model, the source domain training works well with results reaching 0…
YYinn updated
3 months ago
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Dear author,
Sorry to bother you.
According to your open-source code, I reproduced the domain adaptation experiment from Urban to Rural. I cropped the image to a size of 384x384 according to your ex…