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 261–270 of 305 papers

TitleStatusHype
GPT Self-Supervision for a Better Data Annotator—0
HalalNet: A Deep Neural Network that Classifies the Halalness Slaughtered Chicken from their Images—0
Harmonization Across Imaging Locations(HAIL): One-Shot Learning for Brain MRI—0
Harnessing Geometric Constraints from Emotion Labels to improve Face Verification—0
HDTest: Differential Fuzz Testing of Brain-Inspired Hyperdimensional Computing—0
HDXplore: Automated Blackbox Testing of Brain-Inspired Hyperdimensional Computing—0
High-dimensional separability for one- and few-shot learning—0
Improving Knowledge Extraction from LLMs for Task Learning through Agent Analysis—0
Improving One-Shot Learning through Fusing Side Information—0
InsertionNet 2.0: Minimal Contact Multi-Step Insertion Using Multimodal Multiview Sensory Input—0
Show:102550
← PrevPage 27 of 31Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified