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SOTA
少样本图像分类
Few Shot Image Classification On Omniglot 1 2
Few Shot Image Classification On Omniglot 1 2
评估指标
Accuracy
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
Accuracy
Paper Title
Repository
MC2+
99.97
Meta-Curvature
DCN6-E
99.92%
Decoder Choice Network for Meta-Learning
DCN4
99.8%
Decoder Choice Network for Meta-Learning
Relation Net
99.6
Learning to Compare: Relation Network for Few-Shot Learning
iMAML, Hessian-Free
99.50
Meta-Learning with Implicit Gradients
MT-net
99.5
Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace
MAML++
99.47
How to train your MAML
Hyperbolic ProtoNet
99.0
Hyperbolic Image Embeddings
Prototypical Networks
98.8
Prototypical Networks for Few-shot Learning
MAML
98.7
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
VAMPIRE
98.43
Uncertainty in Model-Agnostic Meta-Learning using Variational Inference
adaCNN (DF)
98.42
Rapid Adaptation with Conditionally Shifted Neurons
-
ConvNet with Memory Module
98.4
Learning to Remember Rare Events
Matching Nets
98.1
Matching Networks for One Shot Learning
Neural Statistician
98.1
Towards a Neural Statistician
APL
97.9
Adaptive Posterior Learning: few-shot learning with a surprise-based memory module
Reptile + Transduction
97.68
On First-Order Meta-Learning Algorithms
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Few Shot Image Classification On Omniglot 1 2 | SOTA | HyperAI超神经