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 211–220 of 305 papers

TitleStatusHype
Annotation-Free and One-Shot Learning for Instance Segmentation of Homogeneous Object Clusters—0
A One-Shot Learning Framework for Assessment of Fibrillar Collagen from Second Harmonic Generation Images of an Infarcted Myocardium—0
Application of Computer Vision Techniques for Segregation of PlasticWaste based on Resin Identification Code—0
AROS: Affordance Recognition with One-Shot Human Stances—0
ARTiS: Appearance-based Action Recognition in Task Space for Real-Time Human-Robot Collaboration—0
Assessing Shape Bias Property of Convolutional Neural Networks—0
A System For Robot Concept Learning Through Situated Dialogue—0
Attention-Based Multi-Context Guiding for Few-Shot Semantic Segmentation—0
Augmented Memory Networks for Streaming-Based Active One-Shot Learning—0
Augmented Memory Networks for Streaming-Based Active One-Shot Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified