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 276–300 of 305 papers

TitleStatusHype
Non-Local Representation based Mutual Affine-Transfer Network for Photorealistic StylizationCode0
Active One-shot LearningCode0
Emulating Brain-like Rapid Learning in Neuromorphic Edge ComputingCode0
The Omniglot challenge: a 3-year progress reportCode0
One Shot Learning for Deformable Medical Image Registration and Periodic Motion TrackingCode0
One-shot recognition of any material anywhere using contrastive learning with physics-based renderingCode0
A Kings Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian ApproximationCode0
A Novel Embedding Architecture and Score Level Fusion Scheme for Occluded Image Acquisition in Ear Biometrics SystemCode0
A few-shot learning approach with domain adaptation for personalized real-life stress detection in close relationshipsCode0
Direct Data-Driven Discounted Infinite Horizon Linear Quadratic Regulator with Robustness GuaranteesCode0
Make SVM great again with Siamese kernel for few-shot learningCode0
Deep Triplet Ranking Networks for One-Shot RecognitionCode0
An EMG Gesture Recognition System with Flexible High-Density Sensors and Brain-Inspired High-Dimensional ClassifierCode0
One-shot Learning for Question-Answering in Gaokao History ChallengeCode0
A Named Entity Recognition Corpus for Vietnamese Biomedical Texts to Support Tuberculosis TreatmentCode0
Image Deformation Meta-Networks for One-Shot LearningCode0
Tab2KG: Semantic Table Interpretation with Lightweight Semantic ProfilesCode0
One-Shot Collaborative Data DistillationCode0
Memory-enriched computation and learning in spiking neural networks through Hebbian plasticityCode0
Take Package as Language: Anomaly Detection Using TransformerCode0
MergedNET: A simple approach for one-shot learning in siamese networks based on similarity layersCode0
Variational Prototyping-Encoder: One-Shot Learning with Prototypical ImagesCode0
Meta-Meta Classification for One-Shot LearningCode0
Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual RecognitionCode0
Deep Reinforcement One-Shot Learning for Artificially Intelligent Classification SystemsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified