Sample-Centric Feature Generation for Semi-Supervised Few-Shot Learning-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Sample-Centric Feature Generation for Semi-Supervised Few-Shot Learning

Published:2022 Issue: Volume:31 Page:2309-2320
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Zhang Bo^ORCID,Ye Hancheng^ORCID,Yu Gang^ORCID,Wang Bin^ORCID,Wu Yike,Fan Jiayuan^ORCID,Chen Tao^ORCID

Funder

National Natural Science Foundation of China

Zhejiang Lab Project

Shanghai Municipal Science and Technology Major Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9626658/09729102.pdf?arnumber=9729102

Reference73 articles.

1. Visualizing data using t-SNE;van der maaten;J Mach Learn Res,2008

2. Empirical Bayes transductive meta-learning with synthetic gradients;hu;Proc Int Conf Learn Represent,2020

3. Learning multiple layers of features from tiny images;krizhevsky,2009

4. Meta-learning with differentiable closed-form solvers;bertinetto;Proc Int Conf Learn Represent,2019

5. Instance Credibility Inference for Few-Shot Learning

Cited by 19 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Few-shot learning with long-tailed labels;Pattern Recognition;2024-12

2. A multi-task effectiveness metric and an adaptive co-training method for enhancing learning performance with few samples;Journal of Intelligent Manufacturing;2024-08-12

3. Metric-based meta-learning combined with hyperspectral imaging for rapid detection of adulteration in domain-shifted camel milk powder;LWT;2024-08

4. Slippage Estimation via Few-Shot Learning Based on Wheel-Ruts Images for Wheeled Robots on Loose Soil;IEEE Transactions on Intelligent Transportation Systems;2024-07

5. A single fast Hebbian-like process enabling one-shot class addition in deep neural networks without backbone modification;Frontiers in Neuroscience;2024-06-12

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3