36 citations · 36 across the 4 of their papers we have counts for
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cs.CV2021
Feature Mining: A Novel Training Strategy for Convolutional Neural Network
Tianshu Xie, Xuan Cheng, Xiaomin Wang +3
In this paper, we propose a novel training strategy for convolutional neural network(CNN) named Feature Mining, that aims to strengthen the network's learning of the local feature.…
cs.CV2021
Go Small and Similar: A Simple Output Decay Brings Better Performance
Xuan Cheng, Tianshu Xie, Xiaomin Wang +3
Regularization and data augmentation methods have been widely used and become increasingly indispensable in deep learning training. Researchers who devote themselves to this have c…
cs.CV2021★ 36 cited
Cut-Thumbnail: A Novel Data Augmentation for Convolutional Neural Network
Tianshu Xie, Xuan Cheng, Minghui Liu +3
In this paper, we propose a novel data augmentation strategy named Cut-Thumbnail, that aims to improve the shape bias of the network. We reduce an image to a certain size and repla…