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Few Shot Image Classification On Dirichlet 1

Metrics

1:1 Accuracy

Results

Performance results of various models on this benchmark

Paper Title
BAVARDAGE83.6Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification
alpha-TIM82.5Realistic Evaluation of Transductive Few-Shot Learning
Laplacian-Shot81.6Laplacian Regularized Few-Shot Learning
BDCSPN80.2Prototype Rectification for Few-Shot Learning
Simpleshot80.1SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning
Baseline++79.7A Closer Look at Few-shot Classification
Entropy Minimization74.8A Baseline for Few-Shot Image Classification
ProtoNet74.2Prototypical Networks for Few-shot Learning
LR-ICI73.5Instance Credibility Inference for Few-Shot Learning
PT-MAP67.1Leveraging the Feature Distribution in Transfer-based Few-Shot Learning
MAML64.5Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Versa61.9Meta-Learning Probabilistic Inference For Prediction
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Few Shot Image Classification On Dirichlet 1 | SOTA | HyperAI