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 51–75 of 305 papers

TitleStatusHype
A few-shot learning approach with domain adaptation for personalized real-life stress detection in close relationshipsCode0
MergedNET: A simple approach for one-shot learning in siamese networks based on similarity layersCode0
Learning New Tasks from a Few Examples with Soft-Label PrototypesCode0
Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual RecognitionCode0
Contour Transformer Network for One-shot Segmentation of Anatomical StructuresCode0
Learning Spatially-Adaptive Squeeze-Excitation Networks for Image Synthesis and Image RecognitionCode0
Simultaneous Perturbation Method for Multi-Task Weight Optimization in One-Shot Meta-LearningCode0
Learning Symbolic Task Representation from a Human-Led Demonstration: A Memory to Store, Retrieve, Consolidate, and Forget ExperiencesCode0
JARVix at SemEval-2022 Task 2: It Takes One to Know One? Idiomaticity Detection using Zero and One-Shot LearningCode0
Learning from similarity and information extraction from structured documentsCode0
Learning to learn with backpropagation of Hebbian plasticityCode0
Deep Reinforcement One-Shot Learning for Artificially Intelligent Classification SystemsCode0
Active One-shot LearningCode0
Improving Siamese Networks for One Shot Learning using Kernel Based Activation functionsCode0
BAE-NET: Branched Autoencoder for Shape Co-SegmentationCode0
An EMG Gesture Recognition System with Flexible High-Density Sensors and Brain-Inspired High-Dimensional ClassifierCode0
It's DONE: Direct ONE-shot learning with quantile weight imprintingCode0
Learning to Remember Rare EventsCode0
AutoTinyBERT: Automatic Hyper-parameter Optimization for Efficient Pre-trained Language ModelsCode0
Generalization in Machine Learning via Analytical Learning TheoryCode0
Image Deformation Meta-Networks for One-Shot LearningCode0
For Manifold Learning, Deep Neural Networks can be Locality Sensitive Hash FunctionsCode0
A Named Entity Recognition Corpus for Vietnamese Biomedical Texts to Support Tuberculosis TreatmentCode0
Distilled One-Shot Federated LearningCode0
Few-Shot Knowledge Graph CompletionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified