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
One-Shot Learning on Attributed Sequences—0
Learning Spatially-Adaptive Squeeze-Excitation Networks for Image Synthesis and Image RecognitionCode0
Recursive Least-Squares Estimator-Aided Online Learning for Visual TrackingCode1
Differentiable Wavetable SynthesisCode1
One-Shot Learning from a Demonstration with Hierarchical Latent Language—0
Brain-inspired Cognition in Next Generation Racetrack Memories—0
EfficientWord-Net: An Open Source Hotword Detection Engine based on One-shot LearningCode1
Simultaneous Perturbation Method for Multi-Task Weight Optimization in One-Shot Meta-LearningCode0
One Representative-Shot Learning Using a Population-Driven Template with Application to Brain Connectivity Classification and Evolution PredictionCode0
Self-Supervised Generative Style Transfer for One-Shot Medical Image SegmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified