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

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Showing 126–150 of 305 papers

TitleStatusHype
DeepRING: Learning Roto-translation Invariant Representation for LiDAR based Place Recognition—0
One-Shot Learning for Text-to-SQL Generation—0
Leveraging Weakly Annotated Data for Hate Speech Detection in Code-Mixed Hinglish: A Feasibility-Driven Transfer Learning Approach with Large Language Models—0
Leveraging Siamese Networks for One-Shot Intrusion Detection Model—0
A Model of Zero-Shot Learning of Spoken Language Understanding—0
Modeling Time Series Similarity with Siamese Recurrent Networks—0
Learning to Support: Exploiting Structure Information in Support Sets for One-Shot Learning—0
Learning to Segment Anatomical Structures Accurately from One Exemplar—0
Depression Status Estimation by Deep Learning based Hybrid Multi-Modal Fusion Model—0
Attention-Based Multi-Context Guiding for Few-Shot Semantic Segmentation—0
Demystification of Few-shot and One-shot Learning—0
Memory Matching Networks for One-Shot Image Recognition—0
Lifelong Machine Learning for Topic Modeling and Beyond—0
Little Giants: Exploring the Potential of Small LLMs as Evaluation Metrics in Summarization in the Eval4NLP 2023 Shared Task—0
LLMs are One-Shot URL Classifiers and Explainers—0
Low Data Drug Discovery with One-shot Learning—0
Metalearning with Hebbian Fast Weights—0
Distilled One-Shot Federated Learning—0
DeepWriteSYN: On-Line Handwriting Synthesis via Deep Short-Term Representations—0
Mathematics of Digital Twins and Transfer Learning for PDE Models—0
MAVOT: Memory-Augmented Video Object Tracking—0
Learning similarity measures from data—0
Max-Margin Invariant Features from Transformed Unlabelled Data—0
Measuring Immediate Adaptation Performance for Neural Machine Translation—0
Adaptive Local-Component-aware Graph Convolutional Network for One-shot Skeleton-based Action Recognition—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified