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 161–170 of 305 papers

TitleStatusHype
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
DeepWriteSYN: On-Line Handwriting Synthesis via Deep Short-Term Representations—0
Exploiting Temporal Coherence for Self-Supervised One-shot Video Re-identification—0
Sorted Pooling in Convolutional Networks for One-shot Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified