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 91–100 of 305 papers

TitleStatusHype
A Kings Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian ApproximationCode0
Few-Shot Knowledge Graph CompletionCode0
Deep Triplet Ranking Networks for One-Shot RecognitionCode0
For Manifold Learning, Deep Neural Networks can be Locality Sensitive Hash FunctionsCode0
Fusion Matters: Learning Fusion in Deep Click-through Rate Prediction ModelsCode0
Generalization in Machine Learning via Analytical Learning TheoryCode0
A Feature-based Generalizable Prediction Model for Both Perceptual and Abstract ReasoningCode0
Supervised Learning without Backpropagation using Spike-Timing-Dependent Plasticity for Image RecognitionCode0
JARVix at SemEval-2022 Task 2: It Takes One to Know One? Idiomaticity Detection using Zero and One-Shot LearningCode0
Learning Spatially-Adaptive Squeeze-Excitation Networks for Image Synthesis and Image RecognitionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified