481 citations · 1.2k across the 21 of their papers we have counts for
4 papers · 1 filter
Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization
Zhuoran Yu, Aojun Zhou, Yukun Ma +3
Standard convolutional neural networks(CNNs) require consistent image resolutions in both training and testing phase. However, in practice, testing with smaller image sizes is nece…
HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions
Duo Li, Aojun Zhou, Anbang Yao
MobileNets, a class of top-performing convolutional neural network architectures in terms of accuracy and efficiency trade-off, are increasingly used in many resourceaware vision a…
Deeply-supervised Knowledge Synergy
Dawei Sun, Anbang Yao, Aojun Zhou +1
Convolutional Neural Networks (CNNs) have become deeper and more complicated compared with the pioneering AlexNet. However, current prevailing training scheme follows the previous…
Adversarial Robustness vs Model Compression, or Both?
Shaokai Ye, Kaidi Xu, Sijia Liu +6
It is well known that deep neural networks (DNNs) are vulnerable to adversarial attacks, which are implemented by adding crafted perturbations onto benign examples. Min-max robust…