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

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Showing 221–230 of 305 papers

TitleStatusHype
A Unified approach for Conventional Zero-shot, Generalized Zero-shot and Few-shot Learning—0
Automatic detection of rare pathologies in fundus photographs using few-shot learning—0
AutoTinyBERT: Automatic Hyper-parameter Optimization for Efficient Pre-trained Language Models—0
Better Together: Resnet-50 accuracy with 13 fewer parameters and at 3 speed—0
Bias Testing and Mitigation in LLM-based Code Generation—0
Brain-inspired Cognition in Next Generation Racetrack Memories—0
Can Humans Do Less-Than-One-Shot Learning?—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
Comparison of Maximum Likelihood and GAN-based training of Real NVPs—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified