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 221–230 of 305 papers

TitleStatusHype
Concept Learning through Deep Reinforcement Learning with Memory-Augmented Neural Networks—0
Multimodal One-Shot Learning of Speech and ImagesCode0
A Deep One-Shot Network for Query-based Logo RetrievalCode0
Learning from limited datasets: Implications for Natural Language Generation and Human-Robot Interaction—0
Investigation of using disentangled and interpretable representations with language conditioning for cross-lingual voice conversion—0
O2A: One-shot Observational learning with Action vectors—0
Towards one-shot learning for rare-word translation with external experts—0
One-shot Learning for iEEG Seizure Detection Using End-to-end Binary Operations: Local Binary Patterns with Hyperdimensional Computing—0
On the Adaptability of Unsupervised CNN-Based Deformable Image Registration to Unseen Image Domains—0
Learning to Support: Exploiting Structure Information in Support Sets for One-Shot Learning—0
Show:102550
← PrevPage 23 of 31Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified