HyperAI超神経
ホームニュース最新論文チュートリアルデータセット百科事典SOTALLMモデルGPU ランキング学会
検索
サイトについて
HyperAI超神経

Domain Adaptation On Usps To Mnist

評価指標

Accuracy

評価結果

このベンチマークにおける各モデルのパフォーマンス結果

モデル名
Accuracy
Paper TitleRepository
DRANet97.8DRANet: Disentangling Representation and Adaptation Networks for Unsupervised Cross-Domain Adaptation
DFA-MCD96.6Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment
SRDA (RAN)95.03Learning Smooth Representation for Unsupervised Domain Adaptation
FAMCD98.75Unsupervised domain adaptation using feature aligned maximum classifier discrepancy-
MCD95.7Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
Mean teacher98.07Self-ensembling for visual domain adaptation
CDAN98.0Conditional Adversarial Domain Adaptation
DFA-ENT96.2Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment
MCD+CAT96.3Cluster Alignment with a Teacher for Unsupervised Domain Adaptation
CyCleGAN (Light-weight Calibrator)98.3Light-weight Calibrator: a Separable Component for Unsupervised Domain Adaptation-
FACT98.6FACT: Federated Adversarial Cross Training
SHOT98.4Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
3CATN98.3Cycle-consistent Conditional Adversarial Transfer Networks
DeepJDOT96.4DeepJDOT: Deep Joint Distribution Optimal Transport for Unsupervised Domain Adaptation
0 of 14 row(s) selected.