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 81–90 of 305 papers

TitleStatusHype
Attentive Recurrent ComparatorsCode0
An EMG Gesture Recognition System with Flexible High-Density Sensors and Brain-Inspired High-Dimensional ClassifierCode0
Supervised Learning without Backpropagation using Spike-Timing-Dependent Plasticity for Image RecognitionCode0
Few-Shot Knowledge Graph CompletionCode0
Few-Shot Adversarial Learning of Realistic Neural Talking Head ModelsCode0
For Manifold Learning, Deep Neural Networks can be Locality Sensitive Hash FunctionsCode0
A Kings Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian ApproximationCode0
Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual RecognitionCode0
Multi-level Semantic Feature Augmentation for One-shot LearningCode0
Deep Triplet Ranking Networks for One-Shot RecognitionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified