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 141–150 of 305 papers

TitleStatusHype
Updatable Siamese Tracker with Two-stage One-shot Learning—0
Watershed of Artificial Intelligence: Human Intelligence, Machine Intelligence, and Biological Intelligence—0
Demystification of Few-shot and One-shot Learning—0
Unsupervised Hyperspectral Stimulated Raman Microscopy Image Enhancement: Denoising and Segmentation via One-Shot Deep LearningCode0
One-shot learning for solution operators of partial differential equations—0
HDTest: Differential Fuzz Testing of Brain-Inspired Hyperdimensional Computing—0
For Manifold Learning, Deep Neural Networks can be Locality Sensitive Hash FunctionsCode0
Harnessing Geometric Constraints from Emotion Labels to improve Face Verification—0
One-shot learning for the long term: consolidation with an artificial hippocampal algorithm—0
Continuous Learning in Neural Machine Translation using Bilingual Dictionaries—0
Show:102550
← PrevPage 15 of 31Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified