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 41–50 of 305 papers

TitleStatusHype
Adaptive Image Transformer for One-Shot Object Detection—0
Application of Computer Vision Techniques for Segregation of PlasticWaste based on Resin Identification Code—0
A One-Shot Learning Framework for Assessment of Fibrillar Collagen from Second Harmonic Generation Images of an Infarcted Myocardium—0
DeepRING: Learning Roto-translation Invariant Representation for LiDAR based Place Recognition—0
Compositional Embeddings for Multi-Label One-Shot Learning—0
Comparison of Maximum Likelihood and GAN-based training of Real NVPs—0
Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study—0
DART: Distribution Aware Retinal Transform for Event-based Cameras—0
DeepWriteSYN: On-Line Handwriting Synthesis via Deep Short-Term Representations—0
Demystification of Few-shot and One-shot Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified