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 151–175 of 305 papers

TitleStatusHype
Uncertainty-based Modulation for Lifelong Learning—0
Unsupervised Meta-Learning For Few-Shot Image Classification—0
Unsupervised Noisy Tracklet Person Re-identification—0
Updatable Siamese Tracker with Two-stage One-shot Learning—0
Using Paraphrasing and Memory-Augmented Models to Combat Data Sparsity in Question Interpretation with a Virtual Patient Dialogue System—0
Verbal Programming of Robot Behavior—0
Towards Learning to Imitate from a Single Video Demonstration—0
Visual Imitation with Reinforcement Learning using Recurrent Siamese Networks—0
VOCABULARY-INFORMED VISUAL FEATURE AUGMENTATION FOR ONE-SHOT LEARNING—0
Watershed of Artificial Intelligence: Human Intelligence, Machine Intelligence, and Biological Intelligence—0
Weakly Supervised One-Shot Detection with Attention Similarity Networks—0
What Can ResNet Learn Efficiently, Going Beyond Kernels?—0
Zero-Shot Learning and its Applications from Autonomous Vehicles to COVID-19 Diagnosis: A Review—0
FIGO: Enhanced Fingerprint Identification Approach Using GAN and One Shot Learning Techniques—0
Generative Adversarial Residual Pairwise Networks for One Shot Learning—0
Generative One-Shot Face Recognition—0
Generative One-Shot Learning (GOL): A Semi-Parametric Approach to One-Shot Learning in Autonomous Vision—0
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
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified