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 191–200 of 305 papers

TitleStatusHype
Improving Siamese Networks for One Shot Learning using Kernel Based Activation functionsCode0
Generative One-Shot Face Recognition—0
Compositional Embeddings: Joint Perception and Comparison of Class Label Sets—0
Multimodal Continuation-style Architectures for Human-Robot Interaction—0
Learning in Text Streams: Discovery and Disambiguation of Entity and Relation Instances—0
Augmented Memory Networks for Streaming-Based Active One-Shot Learning—0
A Kings Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian ApproximationCode0
Non-Local Representation based Mutual Affine-Transfer Network for Photorealistic StylizationCode0
Automatic detection of rare pathologies in fundus photographs using few-shot learning—0
One Shot Learning for Deformable Medical Image Registration and Periodic Motion TrackingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified