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 11–20 of 305 papers

TitleStatusHype
BaseTransformers: Attention over base data-points for One Shot LearningCode1
EfficientWord-Net: An Open Source Hotword Detection Engine based on One-shot LearningCode1
Grounded Language Learning Fast and SlowCode1
Latent Diffusion Model-Enabled Low-Latency Semantic Communication in the Presence of Semantic Ambiguities and Wireless Channel NoisesCode1
An In-Depth Evaluation of Federated Learning on Biomedical Natural Language ProcessingCode1
Adjoined Networks: A Training Paradigm with Applications to Network CompressionCode1
CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and GeneralizationCode1
Anatomical Data Augmentation via Fluid-based Image RegistrationCode1
An Overview of Deep Learning Architectures in Few-Shot Learning DomainCode1
Detecting Hate Speech with GPT-3Code1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified