JOURNAL ARTICLE

Generative Probabilistic Meta-Learning for Few-Shot Image Classification

Meijun FuXiaomin WangJun WangYi Zhang

Year: 2024 Journal:   IEEE Transactions on Emerging Topics in Computational Intelligence Vol: 9 (2)Pages: 1947-1960   Publisher: Institute of Electrical and Electronics Engineers
Keywords:
Artificial intelligence Generative grammar Probabilistic logic Computer science Shot (pellet) Pattern recognition (psychology) Meta learning (computer science) Contextual image classification Image (mathematics) Probabilistic classification One shot Machine learning Naive Bayes classifier Support vector machine Task (project management) Engineering

Metrics

2
Cited By
1.28
FWCI (Field Weighted Citation Impact)
47
Refs
0.79
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Domain Adaptation and Few-Shot Learning
Physical Sciences →  Computer Science →  Artificial Intelligence
COVID-19 diagnosis using AI
Health Sciences →  Medicine →  Radiology, Nuclear Medicine and Imaging
Advanced Neural Network Applications
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

Related Documents

JOURNAL ARTICLE

Unsupervised Meta-Learning For Few-Shot Image Classification

Siavash KhodadadehLadislau BölöniMubarak Shah

Journal:   arXiv (Cornell University) Year: 2018 Vol: 32 Pages: 10132-10142
JOURNAL ARTICLE

Few-Shot Directed Meta-Learning for Image Classification

Jihong OuyangGanghai DuanSiguang Liu

Journal:   International Journal of Pattern Recognition and Artificial Intelligence Year: 2022 Vol: 37 (01)
JOURNAL ARTICLE

Prototype Bayesian Meta-Learning for Few-Shot Image Classification

Meijun FuXiaomin WangJun WangYi Zhang

Journal:   IEEE Transactions on Neural Networks and Learning Systems Year: 2024 Vol: 36 (4)Pages: 7010-7024
JOURNAL ARTICLE

MGML: Momentum group meta-learning for few-shot image classification

Xiaomeng ZhuShuxiao Li

Journal:   Neurocomputing Year: 2022 Vol: 514 Pages: 351-361
© 2026 ScienceGate Book Chapters — All rights reserved.