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 131–140 of 305 papers

TitleStatusHype
A Model of Zero-Shot Learning of Spoken Language Understanding—0
Mathematics of Digital Twins and Transfer Learning for PDE Models—0
Learning to Support: Exploiting Structure Information in Support Sets for One-Shot Learning—0
Learning to Segment Anatomical Structures Accurately from One Exemplar—0
Depression Status Estimation by Deep Learning based Hybrid Multi-Modal Fusion Model—0
Attention-Based Multi-Context Guiding for Few-Shot Semantic Segmentation—0
Demystification of Few-shot and One-shot Learning—0
Lifelong Machine Learning for Topic Modeling and Beyond—0
Little Giants: Exploring the Potential of Small LLMs as Evaluation Metrics in Summarization in the Eval4NLP 2023 Shared Task—0
Low Data Drug Discovery with One-shot Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified