HyperAI초신경
홈뉴스최신 연구 논문튜토리얼데이터셋백과사전SOTALLM 모델GPU 랭킹컨퍼런스
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HyperAI초신경

Few Shot Image Classification On Mini 1

평가 지표

Accuracy

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름
Accuracy
Paper TitleRepository
MCT78.55%Meta-Learned Confidence for Few-shot Learning
BD-CSPN70.31%Prototype Rectification for Few-Shot Learning
HyperShot53.18%HyperShot: Few-Shot Learning by Kernel HyperNetworks
R2-D2+Task Aug65.95%Task Augmentation by Rotating for Meta-Learning
AmdimNet76.82%Self-Supervised Learning For Few-Shot Image Classification
MetaOptNet-SVM+Task Aug65.38%Task Augmentation by Rotating for Meta-Learning
GCR53.21Few-Shot Learning with Global Class Representations
Neg-Margin63.85Negative Margin Matters: Understanding Margin in Few-shot Classification
EPNet77.27%Embedding Propagation: Smoother Manifold for Few-Shot Classification
PLATIPUS50.13%Probabilistic Model-Agnostic Meta-Learning
BaseTransformers (Inductive)70.88%BaseTransformers: Attention over base data-points for One Shot Learning
SIB70.0%--
Multiple-semantics67.2%Baby steps towards few-shot learning with multiple semantics-
PT+MAP82.92%Leveraging the Feature Distribution in Transfer-based Few-Shot Learning
DivCoop63.73%Diversity with Cooperation: Ensemble Methods for Few-Shot Classification
Transfer+SGC76.47%Graph-based Interpolation of Feature Vectors for Accurate Few-Shot Classification-
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