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Few Shot Image Classification On Mini 13

Métriques

Accuracy

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Accuracy	Paper Title	Repository
TPN (Higher Shot)	52.8	Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Label Propagation	51.2	Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Transductive CNAPS + FETI	85.9	Enhancing Few-Shot Image Classification with Unlabelled Examples
MAML + Transduction	48.2	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Reptile+BN	47.6	On First-Order Meta-Learning Algorithms
TIM-GD	72.8	Transductive Information Maximization For Few-Shot Learning
Prototypical Networks (Higher Way)	50.1	Prototypical Networks for Few-shot Learning
Transductive CNAPS	59.6	Enhancing Few-Shot Image Classification with Unlabelled Examples
MAML	46.9	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Relation Networks	47.9	Learning to Compare: Relation Network for Few-Shot Learning
Prototypical Networks	49.3	Prototypical Networks for Few-shot Learning
Reptile	44.7	On First-Order Meta-Learning Algorithms
Simple CNAPS	56.7	Improved Few-Shot Visual Classification
Simple CNAPS + FETI	83.1	Improved Few-Shot Visual Classification

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Few Shot Image Classification On Mini 13 | SOTA | HyperAI