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 1–50 of 305 papers

TitleStatusHype
Ludwig: a type-based declarative deep learning toolboxCode3
PsyDT: Using LLMs to Construct the Digital Twin of Psychological Counselor with Personalized Counseling Style for Psychological CounselingCode3
Prototypical Networks for Few-shot LearningCode2
Grounded Language Learning Fast and SlowCode1
One-Shot Learning for Pose-Guided Person Image Synthesis in the WildCode1
BaseTransformers: Attention over base data-points for One Shot LearningCode1
Self-Supervised Generative Style Transfer for One-Shot Medical Image SegmentationCode1
Matching Networks for One Shot LearningCode1
One-Shot Learning for Language ModellingCode1
Recursive Least-Squares Estimator-Aided Online Learning for Visual TrackingCode1
CrossFi: A Cross Domain Wi-Fi Sensing Framework Based on Siamese NetworkCode1
One-Shot Learning for Semantic SegmentationCode1
Adjoined Networks: A Training Paradigm with Applications to Network CompressionCode1
'Less Than One'-Shot Learning: Learning N Classes From M<N SamplesCode1
Efficient implementations of echo state network cross-validationCode1
Dynamic Few-Shot Visual Learning without ForgettingCode1
Latent Diffusion Model-Enabled Low-Latency Semantic Communication in the Presence of Semantic Ambiguities and Wireless Channel NoisesCode1
Anatomical Data Augmentation via Fluid-based Image RegistrationCode1
One Line To Rule Them All: Generating LO-Shot Soft-Label PrototypesCode1
One-Shot Learning as Instruction Data Prospector for Large Language ModelsCode1
One-Shot Recognition of Manufacturing Defects in Steel SurfacesCode1
One-shot Text Field Labeling using Attention and Belief Propagation for Structure Information ExtractionCode1
An Overview of Deep Learning Architectures in Few-Shot Learning DomainCode1
UOD: Universal One-shot Detection of Anatomical LandmarksCode1
EfficientWord-Net: An Open Source Hotword Detection Engine based on One-shot LearningCode1
Model-Agnostic Meta-Learning for Fast Adaptation of Deep NetworksCode1
Typilus: Neural Type HintsCode1
One-Shot Instance SegmentationCode1
CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and GeneralizationCode1
An In-Depth Evaluation of Federated Learning on Biomedical Natural Language ProcessingCode1
Detecting Hate Speech with GPT-3Code1
Differentiable Wavetable SynthesisCode1
Echo-SyncNet: Self-supervised Cardiac View Synchronization in EchocardiographyCode1
Efficient Cross-Validation of Echo State NetworksCode1
FETA: Towards Specializing Foundation Models for Expert Task ApplicationsCode1
Assessing Shape Bias Property of Convolutional Neural Networks—0
A Hippocampus Model for Online One-Shot Storage of Pattern Sequences—0
ARTiS: Appearance-based Action Recognition in Task Space for Real-Time Human-Robot Collaboration—0
AROS: Affordance Recognition with One-Shot Human Stances—0
AHAM: Adapt, Help, Ask, Model -- Harvesting LLMs for literature mining—0
Adaptive Image Transformer for One-Shot Object Detection—0
Application of Computer Vision Techniques for Segregation of PlasticWaste based on Resin Identification Code—0
A One-Shot Learning Framework for Assessment of Fibrillar Collagen from Second Harmonic Generation Images of an Infarcted Myocardium—0
DeepRING: Learning Roto-translation Invariant Representation for LiDAR based Place Recognition—0
Compositional Embeddings for Multi-Label One-Shot Learning—0
Comparison of Maximum Likelihood and GAN-based training of Real NVPs—0
Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study—0
DART: Distribution Aware Retinal Transform for Event-based Cameras—0
DeepWriteSYN: On-Line Handwriting Synthesis via Deep Short-Term Representations—0
Demystification of Few-shot and One-shot Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified