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 121–130 of 305 papers

TitleStatusHype
Learning feed-forward one-shot learners—0
Learning from limited datasets: Implications for Natural Language Generation and Human-Robot Interaction—0
Discovering objects and their relations from entangled scene representations—0
A Hippocampus Model for Online One-Shot Storage of Pattern Sequences—0
Learning in Text Streams: Discovery and Disambiguation of Entity and Relation Instances—0
DeepRING: Learning Roto-translation Invariant Representation for LiDAR based Place Recognition—0
Augmented Memory Networks for Streaming-Based Active One-Shot Learning—0
One-Shot Learning for Text-to-SQL Generation—0
A Model of Zero-Shot Learning of Spoken Language Understanding—0
Learning to Support: Exploiting Structure Information in Support Sets for One-Shot Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified