HyperAIHyperAI
الرئيسيةالمنصةالوثائقالأخبارالأوراق البحثيةالدروسمجموعات البياناتالموسوعةSOTAنماذج LLMلوحة الأداء GPUالفعاليات
البحث
حول
HyperAIHyperAI

Command Palette

Search for a command to run...

Few Shot Image Classification On Cifar Fs 5

المقاييس

Accuracy

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

Paper TitleRepository
PT+MAP+SF+SOT (transductive)89.94 The Self-Optimal-Transport Feature Transform
PT+MAP+SF+BPA (transductive)89.94The Balanced-Pairwise-Affinities Feature Transform
PEMnE-BMS*88.44Squeezing Backbone Feature Distributions to the Max for Efficient Few-Shot Learning
LST+MAP87.79Transfer learning based few-shot classification using optimal transport mapping from preprocessed latent space of backbone neural network
Illumination Augmentation87.73Sill-Net: Feature Augmentation with Separated Illumination Representation
PT+MAP87.69Leveraging the Feature Distribution in Transfer-based Few-Shot Learning
BAVARDAGE87.35Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification-
EASY 3xResNet12 (transductive)87.16EASY: Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients
EASY 2xResNet12 1/√2 (transductive)86.99EASY: Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients
P>M>F (P=DINO-ViT-base, M=ProtoNet)84.3Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference
CAML [Laion-2b]83.3Context-Aware Meta-Learning
pseudo-shots81.87Extended Few-Shot Learning: Exploiting Existing Resources for Novel Tasks
SIB80.0Empirical Bayes Transductive Meta-Learning with Synthetic Gradients
HCTransformers78.89Attribute Surrogates Learning and Spectral Tokens Pooling in Transformers for Few-shot Learning
Adaptive Subspace Network78Adaptive Subspaces for Few-Shot Learning-
Invariance-Equivariance77.87Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning
FewTURE77.76Rethinking Generalization in Few-Shot Classification
R2-D2+Task Aug77.66Task Augmentation by Rotating for Meta-Learning
SKD76.9Self-supervised Knowledge Distillation for Few-shot Learning
MetaOptNet-SVM+Task Aug76.75Task Augmentation by Rotating for Meta-Learning
0 of 38 row(s) selected.