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 21–30 of 305 papers

TitleStatusHype
One-shot Text Field Labeling using Attention and Belief Propagation for Structure Information ExtractionCode1
Grounded Language Learning Fast and SlowCode1
An Overview of Deep Learning Architectures in Few-Shot Learning DomainCode1
One-Shot Learning for Language ModellingCode1
Anatomical Data Augmentation via Fluid-based Image RegistrationCode1
Efficient implementations of echo state network cross-validationCode1
Adjoined Networks: A Training Paradigm with Applications to Network CompressionCode1
One-Shot Recognition of Manufacturing Defects in Steel SurfacesCode1
Typilus: Neural Type HintsCode1
Efficient Cross-Validation of Echo State NetworksCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified