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 261–270 of 305 papers

TitleStatusHype
Improving One-Shot Learning through Fusing Side Information—0
One-Shot Learning for Semantic SegmentationCode1
Continual One-Shot Learning of Hidden Spike-Patterns with Neural Network Simulation Expansion and STDP Convergence Predictions—0
One-Shot Learning in Discriminative Neural Networks—0
The Complex Negotiation Dialogue Game—0
One-Shot Metric Learning for Person Re-Identification—0
Multi-Attention Network for One Shot Learning—0
A Unified approach for Conventional Zero-shot, Generalized Zero-shot and Few-shot Learning—0
Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study—0
Rotation Invariance Neural Network—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified