Conformer: Local Features Coupling Global Representations

Conformer is a dual network structure that combines CNN-based local features with transformer-based global representations for enhanced representation learning.

Data and Resources

Cite this as

Zhiliang Peng, Wei Huang, Lingxi Xie, Yaowei Wang, Shanzhi Gu, Jianbin Jiao, Qixiang Ye (2024). Dataset: Conformer: Local Features Coupling Global Representations. https://doi.org/10.57702/chmps51g

DOI retrieved: December 3, 2024

Additional Info

Field Value
Created December 3, 2024
Last update December 3, 2024
Defined In https://doi.org/10.48550/arXiv.2105.03889
Author Zhiliang Peng
More Authors
Wei Huang
Lingxi Xie
Yaowei Wang
Shanzhi Gu
Jianbin Jiao
Qixiang Ye
Homepage https://github.com/pengzhiliang/Conformer