Memory-Augmented Relation Network for Few-Shot Learning-Reference-Cited by-同舟云学术

Memory-Augmented Relation Network for Few-Shot Learning

Published:2020-10-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 28th ACM International Conference on Multimedia
language:
Short-container-title:

Author:

He Jun¹,Hong Richang¹,Liu Xueliang¹,Xu Mingliang²,Zha Zheng-Jun³,Wang Meng¹

Affiliation:

1. Hefei University of Technology, Hefei, China

2. Zhengzhou University, Zhengzhou, China

3. University of Science and Technology of China, Hefei, China

Funder

National Natural Science Foundation of China

National Key R&D Program of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3394171.3413811

Reference44 articles.

1. Marcin Andrychowicz Misha Denil Sergio Gomez Matthew W Hoffman David Pfau Tom Schaul Brendan Shillingford and Nando De Freitas. 2016. Learning to learn by gradient descent by gradient descent. In Advances in neural information processing systems. 3981--3989. Marcin Andrychowicz Misha Denil Sergio Gomez Matthew W Hoffman David Pfau Tom Schaul Brendan Shillingford and Nando De Freitas. 2016. Learning to learn by gradient descent by gradient descent. In Advances in neural information processing systems. 3981--3989.

2. Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

Cited by 38 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. Bimodal semantic fusion prototypical network for few-shot classification;Information Fusion;2024-09

2. Meta-learning Approaches for Few-Shot Learning: A Survey of Recent Advances;ACM Computing Surveys;2024-07-25

3. Noise-Tolerant Hybrid Prototypical Learning with Noisy Web Data;ACM Transactions on Multimedia Computing, Communications, and Applications;2024-07-08

4. Open DGML: Intrusion Detection Based on Open-Domain Generation Meta-Learning;Applied Sciences;2024-06-22

5. TMNIO:Triplet merged network with involution operators for improved few‐shot image classification;IET Image Processing;2024-02-21