LaSO: Label-Set Operations Networks for Multi-Label Few-Shot Learning-Reference-Cited by-同舟云学术

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LaSO: Label-Set Operations Networks for Multi-Label Few-Shot Learning

Published:2019-06 Issue: Volume: Page:
ISSN:
Container-title:2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Alfassy Amit,Karlinsky Leonid,Aides Amit,Shtok Joseph,Harary Sivan,Feris Rogerio,Giryes Raja,Bronstein Alex M.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8938205/8953184/08954088.pdf?arnumber=8954088

Cited by 78 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. SRL‐ProtoNet: Self‐supervised representation learning for few‐shot remote sensing scene classification;IET Computer Vision;2024-09-02

2. Bi-channel attention meta learning for few-shot fine-grained image recognition;Expert Systems with Applications;2024-05

3. Are Learnable Prompts the Right Way of Prompting? Adapting Vision-and-Language Models with Memory Optimization;IEEE Intelligent Systems;2024-05

4. Pixel Power: Harnessing Image Processing for Optimizing Few-Shot Malicious Traffic Detection;Proceedings of the 2024 2nd Asia Conference on Computer Vision, Image Processing and Pattern Recognition;2024-04-26

5. Learning from Taxonomy: Multi-Label Few-Shot Classification for Everyday Sound Recognition;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

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