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

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Unsupervised Few Shot Image Classification On 2

평가 지표

Accuracy

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름	Accuracy	Paper Title	Repository
BECLR	81.69	BECLR: Batch Enhanced Contrastive Few-Shot Learning	-
UniSiam	69.60	Self-Supervision Can Be a Good Few-Shot Learner	-
LF2CS	53.16	Unsupervised Few-Shot Image Classification by Learning Features into Clustering Space
UBC-FSL	68.0	Shot in the Dark: Few-Shot Learning with No Base-Class Labels	-
HMS	58.42	Revisiting Unsupervised Meta-Learning via the Characteristics of Few-Shot Tasks	-
ULDA	41.77	Diversity Helps: Unsupervised Few-shot Learning via Distribution Shift-based Data Augmentation	-
SAMPTransfer (Conv4)	49.10	Self-Attention Message Passing for Contrastive Few-Shot Learning	-
PL-CFE	49.51	Rethinking Clustering-Based Pseudo-Labeling for Unsupervised Meta-Learning	-
ArL	43.68	Rethinking Class Relations: Absolute-relative Supervised and Unsupervised Few-shot Learning	-
PDA-Net	69.01	Few-Shot Learning with Part Discovery and Augmentation from Unlabeled Images	-
U-MlSo	43.01	Multi-level Second-order Few-shot Learning	-
CPNWCP	45.00	Contrastive Prototypical Network with Wasserstein Confidence Penalty

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Unsupervised Few Shot Image Classification On 2 | SOTA | HyperAI초신경