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 51–100 of 305 papers

TitleStatusHype
Concept Learning through Deep Reinforcement Learning with Memory-Augmented Neural Networks—0
Continual One-Shot Learning of Hidden Spike-Patterns with Neural Network Simulation Expansion and STDP Convergence Predictions—0
Continuous Learning in Neural Machine Translation using Bilingual Dictionaries—0
Contour Primitive of Interest Extraction Network Based on One-Shot Learning for Object-Agnostic Vision Measurement—0
AROS: Affordance Recognition with One-Shot Human Stances—0
Learning from limited datasets: Implications for Natural Language Generation and Human-Robot Interaction—0
Correlation Weighted Prototype-based Self-Supervised One-Shot Segmentation of Medical Images—0
Covariance of Motion and Appearance Featuresfor Spatio Temporal Recognition Tasks—0
Learning in Text Streams: Discovery and Disambiguation of Entity and Relation Instances—0
DART: Distribution Aware Retinal Transform for Event-based Cameras—0
Learning Relational Representations by Analogy using Hierarchical Siamese Networks—0
DeepRING: Learning Roto-translation Invariant Representation for LiDAR based Place Recognition—0
Learning to Support: Exploiting Structure Information in Support Sets for One-Shot Learning—0
Interactive Instance Annotation with Siamese Networks—0
AFAT: Adaptive Failure-Aware Tracker for Robust Visual Object Tracking—0
Inverting The Generator Of A Generative Adversarial Network—0
Brain-inspired Cognition in Next Generation Racetrack Memories—0
Bias Testing and Mitigation in LLM-based Code Generation—0
An Exploration of Three Lightly-supervised Representation Learning Approaches for Named Entity Classification—0
Investigation of using disentangled and interpretable representations with language conditioning for cross-lingual voice conversion—0
Exploring the potential of prototype-based soft-labels data distillation for imbalanced data classification—0
Better Together: Resnet-50 accuracy with 13 fewer parameters and at 3 speed—0
An Event based Prediction Suffix Tree—0
Integrating Diverse Knowledge Sources for Online One-shot Learning of Novel Tasks—0
Meta-Reinforcement Learning with Self-Modifying Networks—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
KIT Lecture Translator: Multilingual Speech Translation with One-Shot Learning—0
High-dimensional separability for one- and few-shot learning—0
Automatic detection of rare pathologies in fundus photographs using few-shot learning—0
Experimentally realized memristive memory augmented neural network—0
Exploiting Temporal Coherence for Self-Supervised One-shot Video Re-identification—0
Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by Stepwise Learning—0
Harnessing Geometric Constraints from Emotion Labels to improve Face Verification—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
Dynamic Spectrum Matching with One-shot Learning—0
Can Humans Do Less-Than-One-Shot Learning?—0
Annotation-Free and One-Shot Learning for Instance Segmentation of Homogeneous Object Clusters—0
FIGO: Enhanced Fingerprint Identification Approach Using GAN and One Shot Learning Techniques—0
Causality-Driven One-Shot Learning for Prostate Cancer Grading from MRI—0
Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study—0
A Unified approach for Conventional Zero-shot, Generalized Zero-shot and Few-shot Learning—0
Generative Adversarial Residual Pairwise Networks for One Shot Learning—0
Generative One-Shot Face Recognition—0
Distributional Modeling on a Diet: One-shot Word Learning from Text Only—0
Augmented Memory Networks for Streaming-Based Active One-Shot Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified