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 141–150 of 305 papers

TitleStatusHype
Application of Computer Vision Techniques for Segregation of PlasticWaste based on Resin Identification Code—0
Resource Constrained Dialog Policy Learning via Differentiable Inductive Logic Programming—0
One-Shot Federated Learning with Neuromorphic Processors—0
Unsupervised One-shot Learning of Both Specific Instances and Generalised Classes with a Hippocampal ArchitectureCode0
One-shot Learning for Temporal Knowledge Graphs—0
Learning from similarity and information extraction from structured documentsCode0
Contour Primitive of Interest Extraction Network Based on One-Shot Learning for Object-Agnostic Vision Measurement—0
One-Shot learning based classification for segregation of plastic waste—0
Distilled One-Shot Federated Learning—0
'Less Than One'-Shot Learning: Learning N Classes From M<N SamplesCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified