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 101–110 of 305 papers

TitleStatusHype
Improving Siamese Networks for One Shot Learning using Kernel Based Activation functionsCode0
Learning from similarity and information extraction from structured documentsCode0
Learning Symbolic Task Representation from a Human-Led Demonstration: A Memory to Store, Retrieve, Consolidate, and Forget ExperiencesCode0
MergedNET: A simple approach for one-shot learning in siamese networks based on similarity layersCode0
A Deep One-Shot Network for Query-based Logo RetrievalCode0
One-Shot Learning of Multi-Step Tasks from Observation via Activity Localization in Auxiliary VideoCode0
DeepRING: Learning Roto-translation Invariant Representation for LiDAR based Place Recognition—0
DART: Distribution Aware Retinal Transform for Event-based Cameras—0
Assessing Shape Bias Property of Convolutional Neural Networks—0
A Hippocampus Model for Online One-Shot Storage of Pattern Sequences—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified