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 271–280 of 305 papers

TitleStatusHype
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
Toward Optimal Run Racing: Application to Deep Learning Calibration—0
Quadruplet Network with One-Shot Learning for Fast Visual Object Tracking—0
Comparison of Maximum Likelihood and GAN-based training of Real NVPs—0
Distributional Modeling on a Diet: One-shot Word Learning from Text Only—0
One-Shot Neural Cross-Lingual Transfer for Paradigm Completion—0
Generative Adversarial Residual Pairwise Networks for One Shot Learning—0
Learning to Remember Rare EventsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified