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 2650 of 305 papers

TitleStatusHype
Efficient implementations of echo state network cross-validationCode1
Adjoined Networks: A Training Paradigm with Applications to Network CompressionCode1
One-Shot Recognition of Manufacturing Defects in Steel SurfacesCode1
Typilus: Neural Type HintsCode1
Efficient Cross-Validation of Echo State NetworksCode1
One-Shot Instance SegmentationCode1
Dynamic Few-Shot Visual Learning without ForgettingCode1
One-Shot Learning for Semantic SegmentationCode1
Model-Agnostic Meta-Learning for Fast Adaptation of Deep NetworksCode1
Matching Networks for One Shot LearningCode1
Adaptive Noise Resilient Keyword Spotting Using One-Shot Learning0
Interactive Instance Annotation with Siamese Networks0
Federated One-Shot Learning with Data Privacy and Objective-Hiding0
Transductive One-Shot Learning Meet Subspace Decomposition0
PVChat: Personalized Video Chat with One-Shot Learning0
Representing Signs as Signs: One-Shot ISLR to Facilitate Functional Sign Language Technologies0
One-Shot Learning for k-SAT0
Mathematics of Digital Twins and Transfer Learning for PDE Models0
The use of large language models to enhance cancer clinical trial educational materials0
Fusion Matters: Learning Fusion in Deep Click-through Rate Prediction ModelsCode0
Take Package as Language: Anomaly Detection Using TransformerCode0
One-Shot Manipulation Strategy Learning by Making Contact Analogies0
Supervised Learning without Backpropagation using Spike-Timing-Dependent Plasticity for Image RecognitionCode0
RePD: Defending Jailbreak Attack through a Retrieval-based Prompt Decomposition Process0
SeqNet: Sequential Networks for One-Shot Traffic Sign Recognition With Transfer LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5Unverified