Li Shen

Research topics

• Domain Adaptation and Few-Shot Learning · 1 paper
• Advanced Neural Network Applications · 1 paper
• Wireless Signal Modulation Classification · 1 paper
• Protein Structure and Dynamics · 1 paper
• Neural Networks and Applications · 1 paper
• Force Microscopy Techniques and Applications · 1 paper

Frequent co-authors

• Jie Hu · 2 papers
• Gang Zheng Sun · 1 paper
• Samuel Albanie · 1 paper
• Gang Sun · 1 paper
• Enhua Wu · 1 paper

Papers

1. Squeeze-and-Excitation Networks2018 · 30,566 citations

   Convolutional neural networks are built upon the convolution operation, which extracts informative features by fusing spatial and channel-wise information together within local receptive fields. In order to boost the representational power of a network, several recent approaches have shown the…

2. Squeeze-and-Excitation NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence · 2019 · 12,714 citations

   The central building block of convolutional neural networks (CNNs) is the convolution operator, which enables networks to construct informative features by fusing both spatial and channel-wise information within local receptive fields at each layer. A broad range of prior research…