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 251–300 of 305 papers

TitleStatusHype
Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by Stepwise Learning—0
Exploring the potential of prototype-based soft-labels data distillation for imbalanced data classification—0
Face Verification and Forgery Detection for Ophthalmic Surgery Images—0
Fast Adaptation in Generative Models with Generative Matching Networks—0
Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template Matching—0
Federated One-Shot Learning with Data Privacy and Objective-Hiding—0
FIGO: Enhanced Fingerprint Identification Approach Using GAN and One Shot Learning Techniques—0
Generative Adversarial Residual Pairwise Networks for One Shot Learning—0
Generative One-Shot Face Recognition—0
Generative One-Shot Learning (GOL): A Semi-Parametric Approach to One-Shot Learning in Autonomous Vision—0
GPT Self-Supervision for a Better Data Annotator—0
HalalNet: A Deep Neural Network that Classifies the Halalness Slaughtered Chicken from their Images—0
Harmonization Across Imaging Locations(HAIL): One-Shot Learning for Brain MRI—0
Harnessing Geometric Constraints from Emotion Labels to improve Face Verification—0
HDTest: Differential Fuzz Testing of Brain-Inspired Hyperdimensional Computing—0
HDXplore: Automated Blackbox Testing of Brain-Inspired Hyperdimensional Computing—0
High-dimensional separability for one- and few-shot learning—0
Improving Knowledge Extraction from LLMs for Task Learning through Agent Analysis—0
Improving One-Shot Learning through Fusing Side Information—0
InsertionNet 2.0: Minimal Contact Multi-Step Insertion Using Multimodal Multiview Sensory Input—0
Interactive Instance Annotation with Siamese Networks—0
Inverting The Generator Of A Generative Adversarial Network—0
Investigation of using disentangled and interpretable representations with language conditioning for cross-lingual voice conversion—0
KIT Lecture Translator: Multilingual Speech Translation with One-Shot Learning—0
Latent Attention For If-Then Program Synthesis—0
Learning feed-forward one-shot learners—0
Learning from limited datasets: Implications for Natural Language Generation and Human-Robot Interaction—0
Learning in Text Streams: Discovery and Disambiguation of Entity and Relation Instances—0
Learning Non-deterministic Representations with Energy-based Ensembles—0
Learning Relational Representations by Analogy using Hierarchical Siamese Networks—0
Learning similarity measures from data—0
Learning to Segment Anatomical Structures Accurately from One Exemplar—0
Learning to Support: Exploiting Structure Information in Support Sets for One-Shot Learning—0
Leveraging Siamese Networks for One-Shot Intrusion Detection Model—0
Leveraging Weakly Annotated Data for Hate Speech Detection in Code-Mixed Hinglish: A Feasibility-Driven Transfer Learning Approach with Large Language Models—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
Mathematics of Digital Twins and Transfer Learning for PDE Models—0
MAVOT: Memory-Augmented Video Object Tracking—0
Max-Margin Invariant Features from Transformed Unlabeled Data—0
Max-Margin Invariant Features from Transformed Unlabelled Data—0
Measuring Immediate Adaptation Performance for Neural Machine Translation—0
MemGEN: Memory is All You Need—0
Memory Matching Networks for One-Shot Image Recognition—0
Metalearning with Hebbian Fast Weights—0
Modeling Time Series Similarity with Siamese Recurrent Networks—0
More than the Sum of Its Parts: Ensembling Backbone Networks for Few-Shot Segmentation—0
Multi-Attention Network for One Shot Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified