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 76–100 of 305 papers

TitleStatusHype
A Named Entity Recognition Corpus for Vietnamese Biomedical Texts to Support Tuberculosis TreatmentCode0
Learning Symbolic Task Representation from a Human-Led Demonstration: A Memory to Store, Retrieve, Consolidate, and Forget ExperiencesCode0
Learning to Remember Rare EventsCode0
Make SVM great again with Siamese kernel for few-shot learningCode0
Encoding Matching Criteria for Cross-domain Deformable Image RegistrationCode0
Abstracted Gaussian Prototypes for One-Shot Concept LearningCode0
An EMG Gesture Recognition System with Flexible High-Density Sensors and Brain-Inspired High-Dimensional ClassifierCode0
Active One-shot LearningCode0
Meta-Meta Classification for One-Shot LearningCode0
Direct Data-Driven Discounted Infinite Horizon Linear Quadratic Regulator with Robustness GuaranteesCode0
Attentive Recurrent ComparatorsCode0
Learning from similarity and information extraction from structured documentsCode0
Improving Siamese Networks for One Shot Learning using Kernel Based Activation functionsCode0
Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identificationCode0
It's DONE: Direct ONE-shot learning with quantile weight imprintingCode0
A Kings Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian ApproximationCode0
Few-Shot Knowledge Graph CompletionCode0
Deep Triplet Ranking Networks for One-Shot RecognitionCode0
For Manifold Learning, Deep Neural Networks can be Locality Sensitive Hash FunctionsCode0
Fusion Matters: Learning Fusion in Deep Click-through Rate Prediction ModelsCode0
Generalization in Machine Learning via Analytical Learning TheoryCode0
A Feature-based Generalizable Prediction Model for Both Perceptual and Abstract ReasoningCode0
Supervised Learning without Backpropagation using Spike-Timing-Dependent Plasticity for Image RecognitionCode0
JARVix at SemEval-2022 Task 2: It Takes One to Know One? Idiomaticity Detection using Zero and One-Shot LearningCode0
Learning Spatially-Adaptive Squeeze-Excitation Networks for Image Synthesis and Image RecognitionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified