计算机科学
块(置换群论)
建筑
分割
计算机视觉
图像分割
人工智能
数学
几何学
艺术
视觉艺术
作者
Zhijie Zhao,Kaixu Chen,Satoshi Yamane
标识
DOI:10.1109/gcce53005.2021.9622008
摘要
There are already many methods based on U-net, however, due to the paricularity of medical images, we need to pay more attention to the target area to perform more detailed segmentation. In this paper, we present a CBAM-Unet++ module, which a more targeted architecture for medical image segmentation. It combines Unet++ and Convolutional block attention module to make it easier for architecture to ignore irrelevant background information, thereby paying more attention to the parts that we want to have.
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