SOTAVerified

One-Shot Learning

One-shot learning is the task of learning information about object categories from a single training example.

( Image credit: Siamese Neural Networks for One-shot Image Recognition )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 291–300 of 305 papers

TitleStatusHype
Image Deformation Meta-Networks for One-Shot LearningCode0
Tab2KG: Semantic Table Interpretation with Lightweight Semantic ProfilesCode0
One-Shot Collaborative Data DistillationCode0
Memory-enriched computation and learning in spiking neural networks through Hebbian plasticityCode0
Take Package as Language: Anomaly Detection Using TransformerCode0
MergedNET: A simple approach for one-shot learning in siamese networks based on similarity layersCode0
Variational Prototyping-Encoder: One-Shot Learning with Prototypical ImagesCode0
Meta-Meta Classification for One-Shot LearningCode0
Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual RecognitionCode0
Deep Reinforcement One-Shot Learning for Artificially Intelligent Classification SystemsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified