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Few Shot Image Classification On Tiered 2

Métriques

Accuracy

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Accuracy	Paper Title	Repository
MAML	34.4	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Reptile+BN	35.3	On First-Order Meta-Learning Algorithms
MAML + Transduction	34.8	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Reptile	33.7	On First-Order Meta-Learning Algorithms
TPN (Higher Shot)	44.8	Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Transductive CNAPS	54.6	Enhancing Few-Shot Image Classification with Unlabelled Examples
Simple CNAPS + FETI	57.1	Improved Few-Shot Visual Classification
Prototypical Networks (Higher Way)	38.6	Prototypical Networks for Few-shot Learning
Prototypical Networks	37.3	Prototypical Networks for Few-shot Learning
Simple CNAPS	48.1	Improved Few-Shot Visual Classification
Label Propagation	39.4	Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Relation Networks	36.3	Learning to Compare: Relation Network for Few-Shot Learning
Transductive CNAPS + FETI	65.1	Enhancing Few-Shot Image Classification with Unlabelled Examples

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