ME-D2N: Multi-Expert Domain Decompositional Network for Cross-Domain Few-Shot Learning-Reference-Cited by-同舟云学术

ME-D2N: Multi-Expert Domain Decompositional Network for Cross-Domain Few-Shot Learning

Published:2022-10-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 30th ACM International Conference on Multimedia
language:
Short-container-title:

Author:

Fu Yuqian¹,Xie Yu¹,Fu Yanwei¹,Chen Jingjing¹,Jiang Yu-Gang¹

Affiliation:

1. Fudan University, Shanghai, China

Funder

National Natural Science Foundation of China Project

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3503161.3547995

Reference59 articles.

1. David Bau Bolei Zhou Aditya Khosla Aude Oliva and Antonio Torralba. 2017. Network dissection: Quantifying interpretability of deep visual representations. In CVPR. 6541--6549. David Bau Bolei Zhou Aditya Khosla Aude Oliva and Antonio Torralba. 2017. Network dissection: Quantifying interpretability of deep visual representations. In CVPR. 6541--6549.

2. A systematic study of the class imbalance problem in convolutional neural networks

3. Jonathon Byrd and Zachary Lipton. 2019. What is the effect of importance weighting in deep learning?. In ICML. PMLR 872--881. Jonathon Byrd and Zachary Lipton. 2019. What is the effect of importance weighting in deep learning?. In ICML. PMLR 872--881.

4. John Cai , Bill Cai , and Shen Sheng Mei . 2021 . DAMSL: Domain Agnostic Meta Score-based Learning. In CVPR. 2591--2595. John Cai, Bill Cai, and Shen Sheng Mei. 2021. DAMSL: Domain Agnostic Meta Score-based Learning. In CVPR. 2591--2595.

5. LUNA: Localizing Unfamiliarity Near Acquaintance for Open-Set Long-Tailed Recognition

Cited by 8 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. Cross-domain prototype similarity correction for few-shot radar modulation signal recognition;Signal Processing;2024-10

2. De-Redundancy Distillation And Feature Shift Correction For Cross-Domain Few-Shot Learning;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

3. Joint data augmentation and knowledge distillation for few-shot continual relation extraction;Applied Intelligence;2024-02

4. Gradient-Guided Channel Masking for Cross-Domain Few-Shot Learning;2024

5. Meta Channel Masking for Cross-Domain Few-Shot Learning;2024