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

Showing 150 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
One-Shot Instance SegmentationCode1
Adjoined Networks: A Training Paradigm with Applications to Network CompressionCode1
Anatomical Data Augmentation via Fluid-based Image RegistrationCode1
Typilus: Neural Type HintsCode1
One-Shot Learning for Language ModellingCode1
One-shot Text Field Labeling using Attention and Belief Propagation for Structure Information ExtractionCode1
Self-Supervised Generative Style Transfer for One-Shot Medical Image SegmentationCode1
FETA: Towards Specializing Foundation Models for Expert Task ApplicationsCode1
EfficientWord-Net: An Open Source Hotword Detection Engine based on One-shot LearningCode1
BaseTransformers: Attention over base data-points for One Shot LearningCode1
Detecting Hate Speech with GPT-3Code1
Matching Networks for One Shot LearningCode1
CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and GeneralizationCode1
One-Shot Learning as Instruction Data Prospector for Large Language ModelsCode1
Differentiable Wavetable SynthesisCode1
One-Shot Learning for Semantic SegmentationCode1
One-Shot Recognition of Manufacturing Defects in Steel SurfacesCode1
Efficient implementations of echo state network cross-validationCode1
Recursive Least-Squares Estimator-Aided Online Learning for Visual TrackingCode1
An Overview of Deep Learning Architectures in Few-Shot Learning DomainCode1
Grounded Language Learning Fast and SlowCode1
'Less Than One'-Shot Learning: Learning N Classes From M<N SamplesCode1
Model-Agnostic Meta-Learning for Fast Adaptation of Deep NetworksCode1
Latent Diffusion Model-Enabled Low-Latency Semantic Communication in the Presence of Semantic Ambiguities and Wireless Channel NoisesCode1
Echo-SyncNet: Self-supervised Cardiac View Synchronization in EchocardiographyCode1
Efficient Cross-Validation of Echo State NetworksCode1
An In-Depth Evaluation of Federated Learning on Biomedical Natural Language ProcessingCode1
One-Shot Learning for Pose-Guided Person Image Synthesis in the WildCode1
Dynamic Few-Shot Visual Learning without ForgettingCode1
CrossFi: A Cross Domain Wi-Fi Sensing Framework Based on Siamese NetworkCode1
UOD: Universal One-shot Detection of Anatomical LandmarksCode1
One Line To Rule Them All: Generating LO-Shot Soft-Label PrototypesCode1
Learning from similarity and information extraction from structured documentsCode0
Learning Spatially-Adaptive Squeeze-Excitation Networks for Image Synthesis and Image RecognitionCode0
JARVix at SemEval-2022 Task 2: It Takes One to Know One? Idiomaticity Detection using Zero and One-Shot LearningCode0
One-Shot Collaborative Data DistillationCode0
Learning New Tasks from a Few Examples with Soft-Label PrototypesCode0
Active Use of Latent Constituency Representation in both Humans and Large Language ModelsCode0
A few-shot learning approach with domain adaptation for personalized real-life stress detection in close relationshipsCode0
Improving Siamese Networks for One Shot Learning using Kernel Based Activation functionsCode0
Supervised Learning without Backpropagation using Spike-Timing-Dependent Plasticity for Image RecognitionCode0
A Feature-based Generalizable Prediction Model for Both Perceptual and Abstract ReasoningCode0
A Novel Embedding Architecture and Score Level Fusion Scheme for Occluded Image Acquisition in Ear Biometrics SystemCode0
Generalization in Machine Learning via Analytical Learning TheoryCode0
It's DONE: Direct ONE-shot learning with quantile weight imprintingCode0
Learning Symbolic Task Representation from a Human-Led Demonstration: A Memory to Store, Retrieve, Consolidate, and Forget ExperiencesCode0
Encoding Matching Criteria for Cross-domain Deformable Image RegistrationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5Unverified