Analysis Regarding The Learning-To-Learn Process In The Implementation Of A Meta-Supervised Algorithm For Few-Shot Learning

被引：3
|
作者：
Rivas-Posada, Eduardo [1 ]
Chacon-Murguia, Mario I. [1 ]
机构：
[1] Inst Tecnol Chihuahua, Tecnol Nacl Mexico, Visual Percept Lab, Chihuahua, Chihuahua, Mexico
来源：
2022 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) | 2022年
关键词：
D O I：
10.1109/IJCNN55064.2022.9892057
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
引用
收藏
页数：8
相关论文
共 50 条
  • [1] Learning to learn for few-shot continual active learning
    Ho, Stella
    Liu, Ming
    Gao, Shang
    Gao, Longxiang
    ARTIFICIAL INTELLIGENCE REVIEW, 2024, 57 (10)
  • [2] Augmenting Few-Shot Learning With Supervised Contrastive Learning
    Lee, Taemin
    Yoo, Sungjoo
    IEEE ACCESS, 2021, 9 : 61466 - 61474
  • [3] Learning to teach and learn for semi-supervised few-shot image classification
    Li, Xinzhe
    Huang, Jianqiang
    Liu, Yaoyao
    Zhou, Qin
    Zheng, Shibao
    Schiele, Bernt
    Sun, Qianru
    COMPUTER VISION AND IMAGE UNDERSTANDING, 2021, 212
  • [4] Learning to Learn to Disambiguate: Meta-Learning for Few-Shot Word Sense Disambiguation
    Holla, Nithin
    Mishra, Pushkar
    Yannakoudakis, Helen
    Shutova, Ekaterina
    FINDINGS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, EMNLP 2020, 2020, : 4517 - 4533
  • [5] Weakly Supervised Few-Shot Segmentation via Meta-Learning
    Gama, Pedro H. T.
    Oliveira, Hugo
    Marcato Jr, Jose
    dos Santos, Jefersson A.
    IEEE TRANSACTIONS ON MULTIMEDIA, 2023, 25 : 1784 - 1797
  • [6] Learning to Learn Dense Gaussian Processes for Few-Shot Learning
    Wang, Ze
    Miao, Zichen
    Zhen, Xiantong
    Qiu, Qiang
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 34 (NEURIPS 2021), 2021, 34
  • [7] Learning to Learn from Corrupted Data for Few-Shot Learning
    An, Yuexuan
    Zhao, Xingyu
    Xue, Hui
    PROCEEDINGS OF THE THIRTY-SECOND INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, IJCAI 2023, 2023, : 3423 - 3431
  • [8] Few-shot disease recognition algorithm based on supervised contrastive learning
    Mu, Jiawei
    Feng, Quan
    Yang, Junqi
    Zhang, Jianhua
    Yang, Sen
    FRONTIERS IN PLANT SCIENCE, 2024, 15
  • [9] Unsupervised meta-learning for few-shot learning
    Xu, Hui
    Wang, Jiaxing
    Li, Hao
    Ouyang, Deqiang
    Shao, Jie
    PATTERN RECOGNITION, 2021, 116
  • [10] Meta-Transfer Learning for Few-Shot Learning
    Sun, Qianru
    Liu, Yaoyao
    Chua, Tat-Seng
    Schiele, Bernt
    2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019), 2019, : 403 - 412
12345