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**Describe the solution you'd like**
It would be nice to have an option for self-training. Self-training is related to active learning but gets labels for queries based on its predictions instead of …
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Hi, based on the results attached, it is
still changing the original architecture of the source image and adding extra objects to the translated image? https://github.com/xXCoffeeColaXc/DiffusionBase…
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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
2 months ago
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Paper : https://arxiv.org/pdf/2103.14843.pdf
## Introduction
오늘 읽어볼 논문은 CVPR 2021년에 소개된 "From Synthetic to Real: Unsupervised Domain Adaptation for Animal Pose Estimation" 입니다.
Synthetic …
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First of all, thanks for the great work.
Recently i have implemented an image-level adaptation from CARLA(a simulator) to real urban scenarios using cycle_gan_model.py. But the results are suboptima…
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=== Evaluating classifier for encoded target domain ===
>>> only source > source and target
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[https://aclweb.org/anthology/papers/W/W19/W19-5009/](https://aclweb.org/anthology/papers/W/W19/W19-5009/)
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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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**Problem statement**
In GeoDCAT-AP 2.0.0 `dct:type` on Data Service is used in three different contexts.
1. [service category](https://semiceu.github.io/GeoDCAT-AP/releases/2.0.0/#data-service-…
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## 論文リンク
https://arxiv.org/abs/1810.00740
## 公開日(yyyy/mm/dd)
2018/10/01
## 概要
adversarial training は汎化性能(この文脈では言葉の使い方が少し難しいが、test の adversarial example に対する精度と test の clean data に対する精度があり、前者の…