典型文献
Differentiable Automatic Data Augmentation by Proximal Update for Medical Image Segmentation
文献摘要：
Dear editor,
This letter presents an automatic data augmentation algorithm for medical image segmentation. To increase the scale and diversity of medical images, we propose a differentiable automatic data augment-ation algorithm based on proximal update by finding an optimal augmentation policy. Specifically, on the one hand, a dedicated search space is designed for the medical image segmentation task. On the other hand, we introduce a proximal differentiable gradient descent strategy to update the data augmentation policy, which would increase the searching efficiency. Results of the experiments indicate that the proposed algorithm significantly outperforms state-of-the-art methods, and search speed is 10 times faster than state-of-the-art methods.
文献关键词：
中图分类号：
作者姓名：
Wenxuan He;Min Liu;Yi Tang;Qinghao Liu;Yaonan Wang
作者机构：
College of Electrical and Information Engineering,Hunan University,Changsha 410082;National Engineering Research Center of Robot Visual Perception and Control Technology,Changsha 410082,China
文献出处：
引用格式：
[1]Wenxuan He;Min Liu;Yi Tang;Qinghao Liu;Yaonan Wang-.Differentiable Automatic Data Augmentation by Proximal Update for Medical Image Segmentation)[J].自动化学报（英文版）,2022(07):1315-1318
A类：
Differentiable
B类：
Automatic,Data,Augmentation,by,Proximal,Update,Medical,Image,Segmentation,Dear,editor,
This,letter,presents,automatic,data,augmentation,algorithm,medical,segmentation,To,increase,scale,diversity,images,we,differentiable,proximal,update,finding,optimal,policy,Specifically,one,hand,dedicated,space,designed,task,On,other,introduce,gradient,descent,strategy,which,would,searching,efficiency,Results,experiments,indicate,that,proposed,significantly,outperforms,state,art,methods,speed,times,faster,than
AB值：
0.597962
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