2.2k citations · 3.1k across the 4 of their papers we have counts for
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cs.CV2018★ 499 cited
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…
cs.CV2017★ 2.2k cited
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…
cs.CV2015★ 329 cited
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…