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 1–10 of 305 papers

TitleStatusHype
PsyDT: Using LLMs to Construct the Digital Twin of Psychological Counselor with Personalized Counseling Style for Psychological CounselingCode3
Ludwig: a type-based declarative deep learning toolboxCode3
Prototypical Networks for Few-shot LearningCode2
One-Shot Learning for Pose-Guided Person Image Synthesis in the WildCode1
CrossFi: A Cross Domain Wi-Fi Sensing Framework Based on Siamese NetworkCode1
Latent Diffusion Model-Enabled Low-Latency Semantic Communication in the Presence of Semantic Ambiguities and Wireless Channel NoisesCode1
One-Shot Learning as Instruction Data Prospector for Large Language ModelsCode1
An In-Depth Evaluation of Federated Learning on Biomedical Natural Language ProcessingCode1
UOD: Universal One-shot Detection of Anatomical LandmarksCode1
CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and GeneralizationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified