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

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Showing 231–240 of 305 papers

TitleStatusHype
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
Deep Reinforcement One-Shot Learning for Artificially Intelligent Classification SystemsCode0
KIT Lecture Translator: Multilingual Speech Translation with One-Shot Learning—0
An Exploration of Three Lightly-supervised Representation Learning Approaches for Named Entity Classification—0
Object Relation Detection Based on One-shot Learning—0
Metalearning with Hebbian Fast Weights—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified