HyperAI초신경

홈 뉴스 최신 연구 논문 튜토리얼 데이터셋 백과사전 SOTA LLM 모델 GPU 랭킹 컨퍼런스

한국어

HyperAI초신경

Domain Adaptation On Imageclef Da

평가 지표

Accuracy

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름	Accuracy	Paper Title	Repository
IDDA (Alexnet)	80.6	Looking back at Labels: A Class based Domain Adaptation Technique
SPL	90.3	Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling
rRevGrad+CAT	80.7	Cluster Alignment with a Teacher for Unsupervised Domain Adaptation
MCC+NWD	90.7	Reusing the Task-specific Classifier as a Discriminator: Discriminator-free Adversarial Domain Adaptation
DDA	88.9	Transfer Learning with Dynamic Distribution Adaptation
DADA	89.3	Dual Adversarial Domain Adaptation
EasyTL	88.2	Easy Transfer Learning By Exploiting Intra-domain Structures
CMKD	94.3	Unsupervised Domain Adaption Harnessing Vision-Language Pre-training
MEDM	88.9	Entropy Minimization vs. Diversity Maximization for Domain Adaptation
DAN	76.9	Learning Transferable Features with Deep Adaptation Networks
CADA-P	88.3	Attending to Discriminative Certainty for Domain Adaptation
GLOT-DR	90.4	Global-Local Regularization Via Distributional Robustness
ASAN	88.6	Bridging Adversarial and Statistical Domain Transfer via Spectral Adaptation Networks
IAFN+ENT	88.9	Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation
DFA-SAFN	90.2	Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment
DFA-ENT	89.1	Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment
CAADA	80.2	Correlation-aware Adversarial Domain Adaptation and Generalization	-

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