2.2k citations · 3.1k across the 4 of their papers we have counts for
4 papers
HiFuse: Hierarchical Multi-Scale Feature Fusion Network for Medical Image Classification
Xiangzuo Huo, Gang Sun, Shengwei Tian +5
Medical image classification has developed rapidly under the impetus of the convolutional neural network (CNN). Due to the fixed size of the receptive field of the convolution kern…
Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks
Jie Hu, Li Shen, Samuel Albanie +2
While the use of bottom-up local operators in convolutional neural networks (CNNs) matches well some of the statistics of natural images, it may also prevent such models from captu…
Squeeze-and-Excitation Networks
Jie Hu, Li Shen, Samuel Albanie +2
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…
Deep Image: Scaling up Image Recognition
Ren Wu, Shengen Yan, Yi Shan +2
We present a state-of-the-art image recognition system, Deep Image, developed using end-to-end deep learning. The key components are a custom-built supercomputer dedicated to deep…