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 131–140 of 305 papers

TitleStatusHype
HDTest: Differential Fuzz Testing of Brain-Inspired Hyperdimensional Computing—0
Harnessing Geometric Constraints from Emotion Labels to improve Face Verification—0
Continual One-Shot Learning of Hidden Spike-Patterns with Neural Network Simulation Expansion and STDP Convergence Predictions—0
Harmonization Across Imaging Locations(HAIL): One-Shot Learning for Brain MRI—0
HalalNet: A Deep Neural Network that Classifies the Halalness Slaughtered Chicken from their Images—0
Concept Learning through Deep Reinforcement Learning with Memory-Augmented Neural Networks—0
Application of Computer Vision Techniques for Segregation of PlasticWaste based on Resin Identification Code—0
Compositional Embeddings: Joint Perception and Comparison of Class Label Sets—0
GPT Self-Supervision for a Better Data Annotator—0
Generative One-Shot Learning (GOL): A Semi-Parametric Approach to One-Shot Learning in Autonomous Vision—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified