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 31–40 of 305 papers

TitleStatusHype
BaseTransformers: Attention over base data-points for One Shot LearningCode1
CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and GeneralizationCode1
Detecting Hate Speech with GPT-3Code1
Differentiable Wavetable SynthesisCode1
Adjoined Networks: A Training Paradigm with Applications to Network CompressionCode1
Assessing Shape Bias Property of Convolutional Neural Networks—0
A Hippocampus Model for Online One-Shot Storage of Pattern Sequences—0
ARTiS: Appearance-based Action Recognition in Task Space for Real-Time Human-Robot Collaboration—0
AROS: Affordance Recognition with One-Shot Human Stances—0
AHAM: Adapt, Help, Ask, Model -- Harvesting LLMs for literature mining—0
Show:102550
← PrevPage 4 of 31Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified