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One-Shot Learning
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One-shot learning is the task of learning information about object categories from a single training example.
<span style="color:grey; opacity: 0.6">( Image credit: Siamese Neural Networks for One-shot Image Recognition )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
One-shot Learning for Question-Answering in Gaokao History Challenge
Dynamic Spectrum Matching with One-shot Learning
A Generative Model For Electron Paths
Dynamic Few-Shot Visual Learning without Forgetting
Memory Matching Networks for One-Shot Image Recognition
Deep Triplet Ranking Networks for One-Shot Recognition
One-Shot Learning using Mixture of Variational Autoencoders: a Generalization Learning approach
Multi-level Semantic Feature Augmentation for One-shot Learning
MemGEN: Memory is All You Need
Assessing Shape Bias Property of Convolutional Neural Networks
An EMG Gesture Recognition System with Flexible High-Density Sensors and Brain-Inspired High-Dimensional Classifier
Generalization in Machine Learning via Analytical Learning Theory
One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning
Annotation-Free and One-Shot Learning for Instance Segmentation of Homogeneous Object Clusters
Weakly Supervised One-Shot Detection with Attention Similarity Networks
MAVOT: Memory-Augmented Video Object Tracking
DART: Distribution Aware Retinal Transform for Event-based Cameras
Max-Margin Invariant Features from Transformed Unlabeled Data
Improving One-Shot Learning through Fusing Side Information
One-Shot Learning for Semantic Segmentation
Continual One-Shot Learning of Hidden Spike-Patterns with Neural Network Simulation Expansion and STDP Convergence Predictions
One-Shot Learning in Discriminative Neural Networks
The Complex Negotiation Dialogue Game
A Unified approach for Conventional Zero-shot, Generalized Zero-shot and Few-shot Learning
Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study
Rotation Invariance Neural Network
Toward Optimal Run Racing: Application to Deep Learning Calibration
Quadruplet Network with One-Shot Learning for Fast Visual Object Tracking
Comparison of Maximum Likelihood and GAN-based training of Real NVPs
Distributional Modeling on a Diet: One-shot Word Learning from Text Only
One-Shot Neural Cross-Lingual Transfer for Paradigm Completion
Generative Adversarial Residual Pairwise Networks for One Shot Learning
Prototypical Networks for Few-shot Learning
Learning to Remember Rare Events
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
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